Tag Archives: temperature

Protecting coral reefs with Nemo-Pi, the underwater monitor

Post Syndicated from Janina Ander original https://www.raspberrypi.org/blog/coral-reefs-nemo-pi/

The German charity Save Nemo works to protect coral reefs, and they are developing Nemo-Pi, an underwater “weather station” that monitors ocean conditions. Right now, you can vote for Save Nemo in the Google.org Impact Challenge.

Nemo-Pi — Save Nemo

Save Nemo

The organisation says there are two major threats to coral reefs: divers, and climate change. To make diving saver for reefs, Save Nemo installs buoy anchor points where diving tour boats can anchor without damaging corals in the process.

reef damaged by anchor
boat anchored at buoy

In addition, they provide dos and don’ts for how to behave on a reef dive.

The Nemo-Pi

To monitor the effects of climate change, and to help divers decide whether conditions are right at a reef while they’re still on shore, Save Nemo is also in the process of perfecting Nemo-Pi.

Nemo-Pi schematic — Nemo-Pi — Save Nemo

This Raspberry Pi-powered device is made up of a buoy, a solar panel, a GPS device, a Pi, and an array of sensors. Nemo-Pi measures water conditions such as current, visibility, temperature, carbon dioxide and nitrogen oxide concentrations, and pH. It also uploads its readings live to a public webserver.

Inside the Nemo-Pi device — Save Nemo
Inside the Nemo-Pi device — Save Nemo
Inside the Nemo-Pi device — Save Nemo

The Save Nemo team is currently doing long-term tests of Nemo-Pi off the coast of Thailand and Indonesia. They are also working on improving the device’s power consumption and durability, and testing prototypes with the Raspberry Pi Zero W.

web dashboard — Nemo-Pi — Save Nemo

The web dashboard showing live Nemo-Pi data

Long-term goals

Save Nemo aims to install a network of Nemo-Pis at shallow reefs (up to 60 metres deep) in South East Asia. Then diving tour companies can check the live data online and decide day-to-day whether tours are feasible. This will lower the impact of humans on reefs and help the local flora and fauna survive.

Coral reefs with fishes

A healthy coral reef

Nemo-Pi data may also be useful for groups lobbying for reef conservation, and for scientists and activists who want to shine a spotlight on the awful effects of climate change on sea life, such as coral bleaching caused by rising water temperatures.

Bleached coral

A bleached coral reef

Vote now for Save Nemo

If you want to help Save Nemo in their mission today, vote for them to win the Google.org Impact Challenge:

  1. Head to the voting web page
  2. Click “Abstimmen” in the footer of the page to vote
  3. Click “JA” in the footer to confirm

Voting is open until 6 June. You can also follow Save Nemo on Facebook or Twitter. We think this organisation is doing valuable work, and that their projects could be expanded to reefs across the globe. It’s fantastic to see the Raspberry Pi being used to help protect ocean life.

The post Protecting coral reefs with Nemo-Pi, the underwater monitor appeared first on Raspberry Pi.

UK soldiers design Raspberry Pi bomb disposal robot

Post Syndicated from Helen Lynn original https://www.raspberrypi.org/blog/uk-soldiers-design-raspberry-pi-bomb-disposal-robot/

Three soldiers in the British Army have used a Raspberry Pi to build an autonomous robot, as part of their Foreman of Signals course.

Meet The Soldiers Revolutionising Bomb Disposal

Three soldiers from Blandford Camp have successfully designed and built an autonomous robot as part of their Foreman of Signals Course at the Dorset Garrison.

Autonomous robots

Forces Radio BFBS carried a story last week about Staff Sergeant Jolley, Sergeant Rana, and Sergeant Paddon, also known as the “Project ROVER” team. As part of their Foreman of Signals training, their task was to design an autonomous robot that can move between two specified points, take a temperature reading, and transmit the information to a remote computer. The team comments that, while semi-autonomous robots have been used as far back as 9/11 for tasks like finding people trapped under rubble, nothing like their robot and on a similar scale currently exists within the British Army.

The ROVER buggy

Their build is named ROVER, which stands for Remote Obstacle aVoiding Environment Robot. It’s a buggy that moves on caterpillar tracks, and it’s tethered; we wonder whether that might be because it doesn’t currently have an on-board power supply. A demo shows the robot moving forward, then changing its path when it encounters an obstacle. The team is using RealVNC‘s remote access software to allow ROVER to send data back to another computer.

Applications for ROVER

Dave Ball, Senior Lecturer in charge of the Foreman of Signals course, comments that the project is “a fantastic opportunity for [the team] to, even only halfway through the course, showcase some of the stuff they’ve learnt and produce something that’s really quite exciting.” The Project ROVER team explains that the possibilities for autonomous robots like this one are extensive: they include mine clearance, bomb disposal, and search-and-rescue campaigns. They point out that existing semi-autonomous hardware is not as easy to program as their build. In contrast, they say, “with the invention of the Raspberry Pi, this has allowed three very inexperienced individuals to program a robot very capable of doing these things.”

We make Raspberry Pi computers because we want building things with technology to be as accessible as possible. So it’s great to see a project like this, made by people who aren’t techy and don’t have a lot of computing experience, but who want to solve a problem and see that the Pi is an affordable and powerful tool that can help.

The post UK soldiers design Raspberry Pi bomb disposal robot appeared first on Raspberry Pi.

Brutus 2: the gaming PC case of your dreams

Post Syndicated from Janina Ander original https://www.raspberrypi.org/blog/brutus-2-gaming-pc-case/

Attention, case modders: take a look at the Brutus 2, an extremely snazzy computer case with a partly transparent, animated side panel that’s powered by a Pi. Daniel Otto and Carsten Lehman have a current crowdfunder for the case; their video is in German, but the looks of the build speak for themselves. There are some truly gorgeous effects here.

der BRUTUS 2 by 3nb Gaming

Vorbestellungen ab sofort auf https://www.startnext.com/brutus2 Weitere Infos zu uns auf: https://3nb.de https://www.facebook.com/3nb.de https://www.instagram.com/3nb.de Über 3nb: – GbR aus Leipzig, gegründet 2017 – wir kommen aus den Bereichen Elektronik und Informatik – erstes Produkt: der Brutus One ein Gaming PC mit transparentem Display in der Seite Kurzinfo Brutus 2: – Markencomputergehäuse für Gaming- /Casemoddingszene – Besonderheit: animiertes Seitenfenster angesteuert mit einem Raspberry Pi – Vorteile von unserem Case: o Case ist einzeln lieferbar und nicht nur als komplett-PC o kein Leistungsverbrauch der Grafikkarte dank integriertem Raspberry Pi o bessere Darstellung von Texten und Grafiken durch unscharfen Hintergrund

What’s case modding?

Case modding just means modifying your computer or gaming console’s case, and it’s very popular in the gaming community. Some mods are functional, while others improve the way the case looks. Lots of dedicated gamers don’t only want a powerful computer, they also want it to look amazing — at home, or at LAN parties and games tournaments.

The Brutus 2 case

The Brutus 2 case is made by Daniel and Carsten’s startup, 3nb electronics, and it’s a product that is officially Powered by Raspberry Pi. Its standout feature is the semi-transparent TFT screen, which lets you play any video clip you choose while keeping your gaming hardware on display. It looks incredibly cool. All the graphics for the case’s screen are handled by a Raspberry Pi, so it doesn’t use any of your main PC’s GPU power and your gaming won’t suffer.

Brutus 2 PC case powered by Raspberry Pi

The software

To use Brutus 2, you just need to run a small desktop application on your PC to choose what you want to display on the case. A number of neat animations are included, and you can upload your own if you want.

So far, the app only runs on Windows, but 3nb electronics are planning to make the code open-source, so you can modify it for other operating systems, or to display other file types. This is true to the spirit of the case modding and Raspberry Pi communities, who love adapting, retrofitting, and overhauling projects and code to fit their needs.

Brutus 2 PC case powered by Raspberry Pi

Daniel and Carsten say that one of their campaign’s stretch goals is to implement more functionality in the Brutus 2 app. So in the future, the case could also show things like CPU temperature, gaming stats, and in-game messages. Of course, there’s nothing stopping you from integrating features like that yourself.

If you have any questions about the case, you can post them directly to Daniel and Carsten here.

The crowdfunding campaign

The Brutus 2 campaign on Startnext is currently halfway to its first funding goal of €10000, with over three weeks to go until it closes. If you’re quick, you still be may be able to snatch one of the early-bird offers. And if your whole guild NEEDS this, that’s OK — there are discounts for bulk orders.

The post Brutus 2: the gaming PC case of your dreams appeared first on Raspberry Pi.

This is a really lovely Raspberry Pi tricorder

Post Syndicated from Helen Lynn original https://www.raspberrypi.org/blog/raspberry-pi-tricorder-prop/

At the moment I’m spending my evenings watching all of Star Trek in order. Yes, I have watched it before (but with some really big gaps). Yes, including the animated series (I’m up to The Terratin Incident). So I’m gratified to find this beautiful The Original Series–style tricorder build.

Star Trek Tricorder with Working Display!

At this year’s Replica Prop Forum showcase, we meet up once again wtih Brian Mix, who brought his new Star Trek TOS Tricorder. This beautiful replica captures the weight and finish of the filming hand prop, and Brian has taken it one step further with some modern-day electronics!

A what now?

If you don’t know what a tricorder is, which I guess is faintly possible, the easiest way I can explain is to steal words that Liz wrote when Recantha made one back in 2013. It’s “a made-up thing used by the crew of the Enterprise to measure stuff, store data, and scout ahead remotely when exploring strange new worlds, seeking out new life and new civilisations, and all that jazz.”

A brief history of Picorders

We’ve seen other Raspberry Pi–based realisations of this iconic device. Recantha’s LEGO-cased tricorder delivered some authentic functionality, including temperature sensors, an ultrasonic distance sensor, a photosensor, and a magnetometer. Michael Hahn’s tricorder for element14’s Sci-Fi Your Pi competition in 2015 packed some similar functions, along with Original Series audio effects, into a neat (albeit non-canon) enclosure.

Brian Mix’s Original Series tricorder

Brian Mix’s tricorder, seen in the video above from Tested at this year’s Replica Prop Forum showcase, is based on a high-quality kit into which, he discovered, a Raspberry Pi just fits. He explains that the kit is the work of the late Steve Horch, a special effects professional who provided props for later Star Trek series, including the classic Deep Space Nine episode Trials and Tribble-ations.

A still from an episode of Star Trek: Deep Space Nine: Jadzia Dax, holding an Original Series-sylte tricorder, speaks with Benjamin Sisko

Dax, equipped for time travel

This episode’s plot required sets and props — including tricorders — replicating the USS Enterprise of The Original Series, and Steve Horch provided many of these. Thus, a tricorder kit from him is about as close to authentic as you can possibly find unless you can get your hands on a screen-used prop. The Pi allows Brian to drive a real display and a speaker: “Being the geek that I am,” he explains, “I set it up to run every single Original Series Star Trek episode.”

Even more wonderful hypothetical tricorders that I would like someone to make

This tricorder is beautiful, and it makes me think how amazing it would be to squeeze in some of the sensor functionality of the devices depicted in the show. Space in the case is tight, but it looks like there might be a little bit of depth to spare — enough for an IMU, maybe, or a temperature sensor. I’m certain the future will bring more Pi tricorder builds, and I, for one, can’t wait. Please tell us in the comments if you’re planning something along these lines, and, well, I suppose some other sci-fi franchises have decent Pi project potential too, so we could probably stand to hear about those.

If you’re commenting, no spoilers please past The Animated Series S1 E11. Thanks.

The post This is a really lovely Raspberry Pi tricorder appeared first on Raspberry Pi.

The Helium Factor and Hard Drive Failure Rates

Post Syndicated from Andy Klein original https://www.backblaze.com/blog/helium-filled-hard-drive-failure-rates/

Seagate Enterprise Capacity 3.5 Helium HDD

In November 2013, the first commercially available helium-filled hard drive was introduced by HGST, a Western Digital subsidiary. The 6 TB drive was not only unique in being helium-filled, it was for the moment, the highest capacity hard drive available. Fast forward a little over 4 years later and 12 TB helium-filled drives are readily available, 14 TB drives can be found, and 16 TB helium-filled drives are arriving soon.

Backblaze has been purchasing and deploying helium-filled hard drives over the past year and we thought it was time to start looking at their failure rates compared to traditional air-filled drives. This post will provide an overview, then we’ll continue the comparison on a regular basis over the coming months.

The Promise and Challenge of Helium Filled Drives

We all know that helium is lighter than air — that’s why helium-filled balloons float. Inside of an air-filled hard drive there are rapidly spinning disk platters that rotate at a given speed, 7200 rpm for example. The air inside adds an appreciable amount of drag on the platters that in turn requires an appreciable amount of additional energy to spin the platters. Replacing the air inside of a hard drive with helium reduces the amount of drag, thereby reducing the amount of energy needed to spin the platters, typically by 20%.

We also know that after a few days, a helium-filled balloon sinks to the ground. This was one of the key challenges in using helium inside of a hard drive: helium escapes from most containers, even if they are well sealed. It took years for hard drive manufacturers to create containers that could contain helium while still functioning as a hard drive. This container innovation allows helium-filled drives to function at spec over the course of their lifetime.

Checking for Leaks

Three years ago, we identified SMART 22 as the attribute assigned to recording the status of helium inside of a hard drive. We have both HGST and Seagate helium-filled hard drives, but only the HGST drives currently report the SMART 22 attribute. It appears the normalized and raw values for SMART 22 currently report the same value, which starts at 100 and goes down.

To date only one HGST drive has reported a value of less than 100, with multiple readings between 94 and 99. That drive continues to perform fine, with no other errors or any correlating changes in temperature, so we are not sure whether the change in value is trying to tell us something or if it is just a wonky sensor.

Helium versus Air-Filled Hard Drives

There are several different ways to compare these two types of drives. Below we decided to use just our 8, 10, and 12 TB drives in the comparison. We did this since we have helium-filled drives in those sizes. We left out of the comparison all of the drives that are 6 TB and smaller as none of the drive models we use are helium-filled. We are open to trying different comparisons. This just seemed to be the best place to start.

Lifetime Hard Drive Failure Rates: Helium vs. Air-Filled Hard Drives table

The most obvious observation is that there seems to be little difference in the Annualized Failure Rate (AFR) based on whether they contain helium or air. One conclusion, given this evidence, is that helium doesn’t affect the AFR of hard drives versus air-filled drives. My prediction is that the helium drives will eventually prove to have a lower AFR. Why? Drive Days.

Let’s go back in time to Q1 2017 when the air-filled drives listed in the table above had a similar number of Drive Days to the current number of Drive Days for the helium drives. We find that the failure rate for the air-filled drives at the time (Q1 2017) was 1.61%. In other words, when the drives were in use a similar number of hours, the helium drives had a failure rate of 1.06% while the failure rate of the air-filled drives was 1.61%.

Helium or Air?

My hypothesis is that after normalizing the data so that the helium and air-filled drives have the same (or similar) usage (Drive Days), the helium-filled drives we use will continue to have a lower Annualized Failure Rate versus the air-filled drives we use. I expect this trend to continue for the next year at least. What side do you come down on? Will the Annualized Failure Rate for helium-filled drives be better than air-filled drives or vice-versa? Or do you think the two technologies will be eventually produce the same AFR over time? Pick a side and we’ll document the results over the next year and see where the data takes us.

The post The Helium Factor and Hard Drive Failure Rates appeared first on Backblaze Blog | Cloud Storage & Cloud Backup.

10 visualizations to try in Amazon QuickSight with sample data

Post Syndicated from Karthik Kumar Odapally original https://aws.amazon.com/blogs/big-data/10-visualizations-to-try-in-amazon-quicksight-with-sample-data/

If you’re not already familiar with building visualizations for quick access to business insights using Amazon QuickSight, consider this your introduction. In this post, we’ll walk through some common scenarios with sample datasets to provide an overview of how you can connect yuor data, perform advanced analysis and access the results from any web browser or mobile device.

The following visualizations are built from the public datasets available in the links below. Before we jump into that, let’s take a look at the supported data sources, file formats and a typical QuickSight workflow to build any visualization.

Which data sources does Amazon QuickSight support?

At the time of publication, you can use the following data methods:

  • Connect to AWS data sources, including:
    • Amazon RDS
    • Amazon Aurora
    • Amazon Redshift
    • Amazon Athena
    • Amazon S3
  • Upload Excel spreadsheets or flat files (CSV, TSV, CLF, and ELF)
  • Connect to on-premises databases like Teradata, SQL Server, MySQL, and PostgreSQL
  • Import data from SaaS applications like Salesforce and Snowflake
  • Use big data processing engines like Spark and Presto

This list is constantly growing. For more information, see Supported Data Sources.

Answers in instants

SPICE is the Amazon QuickSight super-fast, parallel, in-memory calculation engine, designed specifically for ad hoc data visualization. SPICE stores your data in a system architected for high availability, where it is saved until you choose to delete it. Improve the performance of database datasets by importing the data into SPICE instead of using a direct database query. To calculate how much SPICE capacity your dataset needs, see Managing SPICE Capacity.

Typical Amazon QuickSight workflow

When you create an analysis, the typical workflow is as follows:

  1. Connect to a data source, and then create a new dataset or choose an existing dataset.
  2. (Optional) If you created a new dataset, prepare the data (for example, by changing field names or data types).
  3. Create a new analysis.
  4. Add a visual to the analysis by choosing the fields to visualize. Choose a specific visual type, or use AutoGraph and let Amazon QuickSight choose the most appropriate visual type, based on the number and data types of the fields that you select.
  5. (Optional) Modify the visual to meet your requirements (for example, by adding a filter or changing the visual type).
  6. (Optional) Add more visuals to the analysis.
  7. (Optional) Add scenes to the default story to provide a narrative about some aspect of the analysis data.
  8. (Optional) Publish the analysis as a dashboard to share insights with other users.

The following graphic illustrates a typical Amazon QuickSight workflow.

Visualizations created in Amazon QuickSight with sample datasets

Visualizations for a data analyst

Source:  https://data.worldbank.org/

Download and Resources:  https://datacatalog.worldbank.org/dataset/world-development-indicators

Data catalog:  The World Bank invests into multiple development projects at the national, regional, and global levels. It’s a great source of information for data analysts.

The following graph shows the percentage of the population that has access to electricity (rural and urban) during 2000 in Asia, Africa, the Middle East, and Latin America.

The following graph shows the share of healthcare costs that are paid out-of-pocket (private vs. public). Also, you can maneuver over the graph to get detailed statistics at a glance.

Visualizations for a trading analyst

Source:  Deutsche Börse Public Dataset (DBG PDS)

Download and resources:  https://aws.amazon.com/public-datasets/deutsche-boerse-pds/

Data catalog:  The DBG PDS project makes real-time data derived from Deutsche Börse’s trading market systems available to the public for free. This is the first time that such detailed financial market data has been shared freely and continually from the source provider.

The following graph shows the market trend of max trade volume for different EU banks. It builds on the data available on XETRA engines, which is made up of a variety of equities, funds, and derivative securities. This graph can be scrolled to visualize trade for a period of an hour or more.

The following graph shows the common stock beating the rest of the maximum trade volume over a period of time, grouped by security type.

Visualizations for a data scientist

Source:  https://catalog.data.gov/

Download and resources:  https://catalog.data.gov/dataset/road-weather-information-stations-788f8

Data catalog:  Data derived from different sensor stations placed on the city bridges and surface streets are a core information source. The road weather information station has a temperature sensor that measures the temperature of the street surface. It also has a sensor that measures the ambient air temperature at the station each second.

The following graph shows the present max air temperature in Seattle from different RWI station sensors.

The following graph shows the minimum temperature of the road surface at different times, which helps predicts road conditions at a particular time of the year.

Visualizations for a data engineer

Source:  https://www.kaggle.com/

Download and resources:  https://www.kaggle.com/datasnaek/youtube-new/data

Data catalog:  Kaggle has come up with a platform where people can donate open datasets. Data engineers and other community members can have open access to these datasets and can contribute to the open data movement. They have more than 350 datasets in total, with more than 200 as featured datasets. It has a few interesting datasets on the platform that are not present at other places, and it’s a platform to connect with other data enthusiasts.

The following graph shows the trending YouTube videos and presents the max likes for the top 20 channels. This is one of the most popular datasets for data engineers.

The following graph shows the YouTube daily statistics for the max views of video titles published during a specific time period.

Visualizations for a business user

Source:  New York Taxi Data

Download and resources:  https://data.cityofnewyork.us/Transportation/2016-Green-Taxi-Trip-Data/hvrh-b6nb

Data catalog: NYC Open data hosts some very popular open data sets for all New Yorkers. This platform allows you to get involved in dive deep into the data set to pull some useful visualizations. 2016 Green taxi trip dataset includes trip records from all trips completed in green taxis in NYC in 2016. Records include fields capturing pick-up and drop-off dates/times, pick-up and drop-off locations, trip distances, itemized fares, rate types, payment types, and driver-reported passenger counts.

The following graph presents maximum fare amount grouped by the passenger count during a period of time during a day. This can be further expanded to follow through different day of the month based on the business need.

The following graph shows the NewYork taxi data from January 2016, showing the dip in the number of taxis ridden on January 23, 2016 across all types of taxis.

A quick search for that date and location shows you the following news report:

Summary

Using Amazon QuickSight, you can see patterns across a time-series data by building visualizations, performing ad hoc analysis, and quickly generating insights. We hope you’ll give it a try today!

 


Additional Reading

If you found this post useful, be sure to check out Amazon QuickSight Adds Support for Combo Charts and Row-Level Security and Visualize AWS Cloudtrail Logs Using AWS Glue and Amazon QuickSight.


Karthik Odapally is a Sr. Solutions Architect in AWS. His passion is to build cost effective and highly scalable solutions on the cloud. In his spare time, he bakes cookies and cupcakes for family and friends here in the PNW. He loves vintage racing cars.

 

 

 

Pranabesh Mandal is a Solutions Architect in AWS. He has over a decade of IT experience. He is passionate about cloud technology and focuses on Analytics. In his spare time, he likes to hike and explore the beautiful nature and wild life of most divine national parks around the United States alongside his wife.

 

 

 

 

Friday Squid Blogging: Squid Prices Rise as Catch Decreases

Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2018/04/friday_squid_bl_621.html

In Japan:

Last year’s haul sank 15% to 53,000 tons, according to the JF Zengyoren national federation of fishing cooperatives. The squid catch has fallen by half in just two years. The previous low was plumbed in 2016.

Lighter catches have been blamed on changing sea temperatures, which impedes the spawning and growth of the squid. Critics have also pointed to overfishing by North Korean and Chinese fishing boats.

Wholesale prices of flying squid have climbed as a result. Last year’s average price per kilogram came to 564 yen, a roughly 80% increase from two years earlier, according to JF Zengyoren.

As usual, you can also use this squid post to talk about the security stories in the news that I haven’t covered.

Read my blog posting guidelines here.

Friday Squid Blogging: Market Squid in Alaskan Waters

Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2018/03/friday_squid_bl_618.html

Rising sea temperatures is causing market squid to move north into Alaskan waters.

As usual, you can also use this squid post to talk about the security stories in the news that I haven’t covered.

Read my blog posting guidelines here.

Take home Mugsy, the Raspberry Pi coffee robot

Post Syndicated from Alex Bate original https://www.raspberrypi.org/blog/mugsy/

We love Mugsy, the Raspberry Pi coffee robot that has smashed its crowdfunding goal within days! Our latest YouTube video shows our catch-up with Mugsy and its creator Matthew Oswald at Maker Faire New York last year.

MUGSY THE RASPBERRY PI COFFEE ROBOT #MFNYC

Uploaded by Raspberry Pi on 2018-03-22.

Mugsy

Labelled ‘the world’s first hackable, customisable, dead simple, robotic coffee maker’, Mugsy allows you to take control of every aspect of the coffee-making process: from grind size and water temperature, to brew and bloom time. Feeling lazy instead? Read in your beans’ barcode via an onboard scanner, and it will automatically use the best settings for your brew.

Mugsy Raspberry Pi Coffee Robot

Looking to start your day with your favourite coffee straight out of bed? Send the robot a text, email, or tweet, and it will notify you when your coffee is ready!

Learning through product development

“Initially, I used [Mugsy] as a way to teach myself hardware design,” explained Matthew at his Editor’s Choice–winning Maker Faire stand. “I really wanted to hold something tangible in my hands. By using the Raspberry Pi and just being curious, anytime I wanted to use a new technology, I would try to pull back [and ask] ‘How can I integrate this into Mugsy?’”

Mugsy Raspberry Pi Coffee Robot

By exploring his passions and using Mugsy as his guinea pig, Matthew created a project that not only solves a problem — how to make amazing coffee at home — but also brings him one step closer to ‘making things’ for a living. “I used to dream about this stuff when I was a kid, and I used to say ‘I’m never going to be able to do something like that.’” he admitted. But now, with open-source devices like the Raspberry Pi so readily available, he “can see the end of the road”: making his passion his livelihood.

Back Mugsy

With only a few days left on the Kickstarter campaign, Mugsy has reached its goal and then some. It’s available for backing from $150 if you provide your own Raspberry Pi 3, or from $175 with a Pi included — check it out today!

The post Take home Mugsy, the Raspberry Pi coffee robot appeared first on Raspberry Pi.

Raspberry Pi 3 Model B+ on sale now at $35

Post Syndicated from Eben Upton original https://www.raspberrypi.org/blog/raspberry-pi-3-model-bplus-sale-now-35/

Here’s a long post. We think you’ll find it interesting. If you don’t have time to read it all, we recommend you watch this video, which will fill you in with everything you need, and then head straight to the product page to fill yer boots. (We recommend the video anyway, even if you do have time for a long read. ‘Cos it’s fab.)

A BRAND-NEW PI FOR π DAY

Raspberry Pi 3 Model B+ is now on sale now for $35, featuring: – A 1.4GHz 64-bit quad-core ARM Cortex-A53 CPU – Dual-band 802.11ac wireless LAN and Bluetooth 4.2 – Faster Ethernet (Gigabit Ethernet over USB 2.0) – Power-over-Ethernet support (with separate PoE HAT) – Improved PXE network and USB mass-storage booting – Improved thermal management Alongside a 200MHz increase in peak CPU clock frequency, we have roughly three times the wired and wireless network throughput, and the ability to sustain high performance for much longer periods.

If you’ve been a Raspberry Pi watcher for a while now, you’ll have a bit of a feel for how we update our products. Just over two years ago, we released Raspberry Pi 3 Model B. This was our first 64-bit product, and our first product to feature integrated wireless connectivity. Since then, we’ve sold over nine million Raspberry Pi 3 units (we’ve sold 19 million Raspberry Pis in total), which have been put to work in schools, homes, offices and factories all over the globe.

Those Raspberry Pi watchers will know that we have a history of releasing improved versions of our products a couple of years into their lives. The first example was Raspberry Pi 1 Model B+, which added two additional USB ports, introduced our current form factor, and rolled up a variety of other feedback from the community. Raspberry Pi 2 didn’t get this treatment, of course, as it was superseded after only one year; but it feels like it’s high time that Raspberry Pi 3 received the “plus” treatment.

So, without further ado, Raspberry Pi 3 Model B+ is now on sale for $35 (the same price as the existing Raspberry Pi 3 Model B), featuring:

  • A 1.4GHz 64-bit quad-core ARM Cortex-A53 CPU
  • Dual-band 802.11ac wireless LAN and Bluetooth 4.2
  • Faster Ethernet (Gigabit Ethernet over USB 2.0)
  • Power-over-Ethernet support (with separate PoE HAT)
  • Improved PXE network and USB mass-storage booting
  • Improved thermal management

Alongside a 200MHz increase in peak CPU clock frequency, we have roughly three times the wired and wireless network throughput, and the ability to sustain high performance for much longer periods.

Behold the shiny

Raspberry Pi 3B+ is available to buy today from our network of Approved Resellers.

New features, new chips

Roger Thornton did the design work on this revision of the Raspberry Pi. Here, he and I have a chat about what’s new.

Introducing the Raspberry Pi 3 Model B+

Raspberry Pi 3 Model B+ is now on sale now for $35, featuring: – A 1.4GHz 64-bit quad-core ARM Cortex-A53 CPU – Dual-band 802.11ac wireless LAN and Bluetooth 4.2 – Faster Ethernet (Gigabit Ethernet over USB 2.0) – Power-over-Ethernet support (with separate PoE HAT) – Improved PXE network and USB mass-storage booting – Improved thermal management Alongside a 200MHz increase in peak CPU clock frequency, we have roughly three times the wired and wireless network throughput, and the ability to sustain high performance for much longer periods.

The new product is built around BCM2837B0, an updated version of the 64-bit Broadcom application processor used in Raspberry Pi 3B, which incorporates power integrity optimisations, and a heat spreader (that’s the shiny metal bit you can see in the photos). Together these allow us to reach higher clock frequencies (or to run at lower voltages to reduce power consumption), and to more accurately monitor and control the temperature of the chip.

Dual-band wireless LAN and Bluetooth are provided by the Cypress CYW43455 “combo” chip, connected to a Proant PCB antenna similar to the one used on Raspberry Pi Zero W. Compared to its predecessor, Raspberry Pi 3B+ delivers somewhat better performance in the 2.4GHz band, and far better performance in the 5GHz band, as demonstrated by these iperf results from LibreELEC developer Milhouse.

Tx bandwidth (Mb/s) Rx bandwidth (Mb/s)
Raspberry Pi 3B 35.7 35.6
Raspberry Pi 3B+ (2.4GHz) 46.7 46.3
Raspberry Pi 3B+ (5GHz) 102 102

The wireless circuitry is encapsulated under a metal shield, rather fetchingly embossed with our logo. This has allowed us to certify the entire board as a radio module under FCC rules, which in turn will significantly reduce the cost of conformance testing Raspberry Pi-based products.

We’ll be teaching metalwork next.

Previous Raspberry Pi devices have used the LAN951x family of chips, which combine a USB hub and 10/100 Ethernet controller. For Raspberry Pi 3B+, Microchip have supported us with an upgraded version, LAN7515, which supports Gigabit Ethernet. While the USB 2.0 connection to the application processor limits the available bandwidth, we still see roughly a threefold increase in throughput compared to Raspberry Pi 3B. Again, here are some typical iperf results.

Tx bandwidth (Mb/s) Rx bandwidth (Mb/s)
Raspberry Pi 3B 94.1 95.5
Raspberry Pi 3B+ 315 315

We use a magjack that supports Power over Ethernet (PoE), and bring the relevant signals to a new 4-pin header. We will shortly launch a PoE HAT which can generate the 5V necessary to power the Raspberry Pi from the 48V PoE supply.

There… are… four… pins!

Coming soon to a Raspberry Pi 3B+ near you

Raspberry Pi 3B was our first product to support PXE Ethernet boot. Testing it in the wild shook out a number of compatibility issues with particular switches and traffic environments. Gordon has rolled up fixes for all known issues into the BCM2837B0 boot ROM, and PXE boot is now enabled by default.

Clocking, voltages and thermals

The improved power integrity of the BCM2837B0 package, and the improved regulation accuracy of our new MaxLinear MxL7704 power management IC, have allowed us to tune our clocking and voltage rules for both better peak performance and longer-duration sustained performance.

Below 70°C, we use the improvements to increase the core frequency to 1.4GHz. Above 70°C, we drop to 1.2GHz, and use the improvements to decrease the core voltage, increasing the period of time before we reach our 80°C thermal throttle; the reduction in power consumption is such that many use cases will never reach the throttle. Like a modern smartphone, we treat the thermal mass of the device as a resource, to be spent carefully with the goal of optimising user experience.

This graph, courtesy of Gareth Halfacree, demonstrates that Raspberry Pi 3B+ runs faster and at a lower temperature for the duration of an eight‑minute quad‑core Sysbench CPU test.

Note that Raspberry Pi 3B+ does consume substantially more power than its predecessor. We strongly encourage you to use a high-quality 2.5A power supply, such as the official Raspberry Pi Universal Power Supply.

FAQs

We’ll keep updating this list over the next couple of days, but here are a few to get you started.

Are you discontinuing earlier Raspberry Pi models?

No. We have a lot of industrial customers who will want to stick with the existing products for the time being. We’ll keep building these models for as long as there’s demand. Raspberry Pi 1B+, Raspberry Pi 2B, and Raspberry Pi 3B will continue to sell for $25, $35, and $35 respectively.

What about Model A+?

Raspberry Pi 1A+ continues to be the $20 entry-level “big” Raspberry Pi for the time being. We are considering the possibility of producing a Raspberry Pi 3A+ in due course.

What about the Compute Module?

CM1, CM3 and CM3L will continue to be available. We may offer versions of CM3 and CM3L with BCM2837B0 in due course, depending on customer demand.

Are you still using VideoCore?

Yes. VideoCore IV 3D is the only publicly-documented 3D graphics core for ARM‑based SoCs, and we want to make Raspberry Pi more open over time, not less.

Credits

A project like this requires a vast amount of focused work from a large team over an extended period. Particular credit is due to Roger Thornton, who designed the board and ran the exhaustive (and exhausting) RF compliance campaign, and to the team at the Sony UK Technology Centre in Pencoed, South Wales. A partial list of others who made major direct contributions to the BCM2837B0 chip program, CYW43455 integration, LAN7515 and MxL7704 developments, and Raspberry Pi 3B+ itself follows:

James Adams, David Armour, Jonathan Bell, Maria Blazquez, Jamie Brogan-Shaw, Mike Buffham, Rob Campling, Cindy Cao, Victor Carmon, KK Chan, Nick Chase, Nigel Cheetham, Scott Clark, Nigel Clift, Dominic Cobley, Peter Coyle, John Cronk, Di Dai, Kurt Dennis, David Doyle, Andrew Edwards, Phil Elwell, John Ferdinand, Doug Freegard, Ian Furlong, Shawn Guo, Philip Harrison, Jason Hicks, Stefan Ho, Andrew Hoare, Gordon Hollingworth, Tuomas Hollman, EikPei Hu, James Hughes, Andy Hulbert, Anand Jain, David John, Prasanna Kerekoppa, Shaik Labeeb, Trevor Latham, Steve Le, David Lee, David Lewsey, Sherman Li, Xizhe Li, Simon Long, Fu Luo Larson, Juan Martinez, Sandhya Menon, Ben Mercer, James Mills, Max Passell, Mark Perry, Eric Phiri, Ashwin Rao, Justin Rees, James Reilly, Matt Rowley, Akshaye Sama, Ian Saturley, Serge Schneider, Manuel Sedlmair, Shawn Shadburn, Veeresh Shivashimper, Graham Smith, Ben Stephens, Mike Stimson, Yuree Tchong, Stuart Thomson, John Wadsworth, Ian Watch, Sarah Williams, Jason Zhu.

If you’re not on this list and think you should be, please let me know, and accept my apologies.

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The Challenges of Opening a Data Center — Part 1

Post Syndicated from Roderick Bauer original https://www.backblaze.com/blog/choosing-data-center/

Backblaze storage pod in new data center

This is part one of a series. The second part will be posted later this week. Use the Join button above to receive notification of future posts in this series.

Though most of us have never set foot inside of a data center, as citizens of a data-driven world we nonetheless depend on the services that data centers provide almost as much as we depend on a reliable water supply, the electrical grid, and the highway system. Every time we send a tweet, post to Facebook, check our bank balance or credit score, watch a YouTube video, or back up a computer to the cloud we are interacting with a data center.

In this series, The Challenges of Opening a Data Center, we’ll talk in general terms about the factors that an organization needs to consider when opening a data center and the challenges that must be met in the process. Many of the factors to consider will be similar for opening a private data center or seeking space in a public data center, but we’ll assume for the sake of this discussion that our needs are more modest than requiring a data center dedicated solely to our own use (i.e. we’re not Google, Facebook, or China Telecom).

Data center technology and management are changing rapidly, with new approaches to design and operation appearing every year. This means we won’t be able to cover everything happening in the world of data centers in our series, however, we hope our brief overview proves useful.

What is a Data Center?

A data center is the structure that houses a large group of networked computer servers typically used by businesses, governments, and organizations for the remote storage, processing, or distribution of large amounts of data.

While many organizations will have computing services in the same location as their offices that support their day-to-day operations, a data center is a structure dedicated to 24/7 large-scale data processing and handling.

Depending on how you define the term, there are anywhere from a half million data centers in the world to many millions. While it’s possible to say that an organization’s on-site servers and data storage can be called a data center, in this discussion we are using the term data center to refer to facilities that are expressly dedicated to housing computer systems and associated components, such as telecommunications and storage systems. The facility might be a private center, which is owned or leased by one tenant only, or a shared data center that offers what are called “colocation services,” and rents space, services, and equipment to multiple tenants in the center.

A large, modern data center operates around the clock, placing a priority on providing secure and uninterrrupted service, and generally includes redundant or backup power systems or supplies, redundant data communication connections, environmental controls, fire suppression systems, and numerous security devices. Such a center is an industrial-scale operation often using as much electricity as a small town.

Types of Data Centers

There are a number of ways to classify data centers according to how they will be used, whether they are owned or used by one or multiple organizations, whether and how they fit into a topology of other data centers; which technologies and management approaches they use for computing, storage, cooling, power, and operations; and increasingly visible these days: how green they are.

Data centers can be loosely classified into three types according to who owns them and who uses them.

Exclusive Data Centers are facilities wholly built, maintained, operated and managed by the business for the optimal operation of its IT equipment. Some of these centers are well-known companies such as Facebook, Google, or Microsoft, while others are less public-facing big telecoms, insurance companies, or other service providers.

Managed Hosting Providers are data centers managed by a third party on behalf of a business. The business does not own data center or space within it. Rather, the business rents IT equipment and infrastructure it needs instead of investing in the outright purchase of what it needs.

Colocation Data Centers are usually large facilities built to accommodate multiple businesses within the center. The business rents its own space within the data center and subsequently fills the space with its IT equipment, or possibly uses equipment provided by the data center operator.

Backblaze, for example, doesn’t own its own data centers but colocates in data centers owned by others. As Backblaze’s storage needs grow, Backblaze increases the space it uses within a given data center and/or expands to other data centers in the same or different geographic areas.

Availability is Key

When designing or selecting a data center, an organization needs to decide what level of availability is required for its services. The type of business or service it provides likely will dictate this. Any organization that provides real-time and/or critical data services will need the highest level of availability and redundancy, as well as the ability to rapidly failover (transfer operation to another center) when and if required. Some organizations require multiple data centers not just to handle the computer or storage capacity they use, but to provide alternate locations for operation if something should happen temporarily or permanently to one or more of their centers.

Organizations operating data centers that can’t afford any downtime at all will typically operate data centers that have a mirrored site that can take over if something happens to the first site, or they operate a second site in parallel to the first one. These data center topologies are called Active/Passive, and Active/Active, respectively. Should disaster or an outage occur, disaster mode would dictate immediately moving all of the primary data center’s processing to the second data center.

While some data center topologies are spread throughout a single country or continent, others extend around the world. Practically, data transmission speeds put a cap on centers that can be operated in parallel with the appearance of simultaneous operation. Linking two data centers located apart from each other — say no more than 60 miles to limit data latency issues — together with dark fiber (leased fiber optic cable) could enable both data centers to be operated as if they were in the same location, reducing staffing requirements yet providing immediate failover to the secondary data center if needed.

This redundancy of facilities and ensured availability is of paramount importance to those needing uninterrupted data center services.

Active/Passive Data Centers

Active/Active Data Centers

LEED Certification

Leadership in Energy and Environmental Design (LEED) is a rating system devised by the United States Green Building Council (USGBC) for the design, construction, and operation of green buildings. Facilities can achieve ratings of certified, silver, gold, or platinum based on criteria within six categories: sustainable sites, water efficiency, energy and atmosphere, materials and resources, indoor environmental quality, and innovation and design.

Green certification has become increasingly important in data center design and operation as data centers require great amounts of electricity and often cooling water to operate. Green technologies can reduce costs for data center operation, as well as make the arrival of data centers more amenable to environmentally-conscious communities.

The ACT, Inc. data center in Iowa City, Iowa was the first data center in the U.S. to receive LEED-Platinum certification, the highest level available.

ACT Data Center exterior

ACT Data Center exterior

ACT Data Center interior

ACT Data Center interior

Factors to Consider When Selecting a Data Center

There are numerous factors to consider when deciding to build or to occupy space in a data center. Aspects such as proximity to available power grids, telecommunications infrastructure, networking services, transportation lines, and emergency services can affect costs, risk, security and other factors that need to be taken into consideration.

The size of the data center will be dictated by the business requirements of the owner or tenant. A data center can occupy one room of a building, one or more floors, or an entire building. Most of the equipment is often in the form of servers mounted in 19 inch rack cabinets, which are usually placed in single rows forming corridors (so-called aisles) between them. This allows staff access to the front and rear of each cabinet. Servers differ greatly in size from 1U servers (i.e. one “U” or “RU” rack unit measuring 44.50 millimeters or 1.75 inches), to Backblaze’s Storage Pod design that fits a 4U chassis, to large freestanding storage silos that occupy many square feet of floor space.

Location

Location will be one of the biggest factors to consider when selecting a data center and encompasses many other factors that should be taken into account, such as geological risks, neighboring uses, and even local flight paths. Access to suitable available power at a suitable price point is often the most critical factor and the longest lead time item, followed by broadband service availability.

With more and more data centers available providing varied levels of service and cost, the choices increase each year. Data center brokers can be employed to find a data center, just as one might use a broker for home or other commercial real estate.

Websites listing available colocation space, such as upstack.io, or entire data centers for sale or lease, are widely used. A common practice is for a customer to publish its data center requirements, and the vendors compete to provide the most attractive bid in a reverse auction.

Business and Customer Proximity

The center’s closeness to a business or organization may or may not be a factor in the site selection. The organization might wish to be close enough to manage the center or supervise the on-site staff from a nearby business location. The location of customers might be a factor, especially if data transmission speeds and latency are important, or the business or customers have regulatory, political, tax, or other considerations that dictate areas suitable or not suitable for the storage and processing of data.

Climate

Local climate is a major factor in data center design because the climatic conditions dictate what cooling technologies should be deployed. In turn this impacts uptime and the costs associated with cooling, which can total as much as 50% or more of a center’s power costs. The topology and the cost of managing a data center in a warm, humid climate will vary greatly from managing one in a cool, dry climate. Nevertheless, data centers are located in both extremely cold regions and extremely hot ones, with innovative approaches used in both extremes to maintain desired temperatures within the center.

Geographic Stability and Extreme Weather Events

A major obvious factor in locating a data center is the stability of the actual site as regards weather, seismic activity, and the likelihood of weather events such as hurricanes, as well as fire or flooding.

Backblaze’s Sacramento data center describes its location as one of the most stable geographic locations in California, outside fault zones and floodplains.

Sacramento Data Center

Sometimes the location of the center comes first and the facility is hardened to withstand anticipated threats, such as Equinix’s NAP of the Americas data center in Miami, one of the largest single-building data centers on the planet (six stories and 750,000 square feet), which is built 32 feet above sea level and designed to withstand category 5 hurricane winds.

Equinix Data Center in Miami

Equinix “NAP of the Americas” Data Center in Miami

Most data centers don’t have the extreme protection or history of the Bahnhof data center, which is located inside the ultra-secure former nuclear bunker Pionen, in Stockholm, Sweden. It is buried 100 feet below ground inside the White Mountains and secured behind 15.7 in. thick metal doors. It prides itself on its self-described “Bond villain” ambiance.

Bahnhof Data Center under White Mountain in Stockholm

Usually, the data center owner or tenant will want to take into account the balance between cost and risk in the selection of a location. The Ideal quadrant below is obviously favored when making this compromise.

Cost vs Risk in selecting a data center

Cost = Construction/lease, power, bandwidth, cooling, labor, taxes
Risk = Environmental (seismic, weather, water, fire), political, economic

Risk mitigation also plays a strong role in pricing. The extent to which providers must implement special building techniques and operating technologies to protect the facility will affect price. When selecting a data center, organizations must make note of the data center’s certification level on the basis of regulatory requirements in the industry. These certifications can ensure that an organization is meeting necessary compliance requirements.

Power

Electrical power usually represents the largest cost in a data center. The cost a service provider pays for power will be affected by the source of the power, the regulatory environment, the facility size and the rate concessions, if any, offered by the utility. At higher level tiers, battery, generator, and redundant power grids are a required part of the picture.

Fault tolerance and power redundancy are absolutely necessary to maintain uninterrupted data center operation. Parallel redundancy is a safeguard to ensure that an uninterruptible power supply (UPS) system is in place to provide electrical power if necessary. The UPS system can be based on batteries, saved kinetic energy, or some type of generator using diesel or another fuel. The center will operate on the UPS system with another UPS system acting as a backup power generator. If a power outage occurs, the additional UPS system power generator is available.

Many data centers require the use of independent power grids, with service provided by different utility companies or services, to prevent against loss of electrical service no matter what the cause. Some data centers have intentionally located themselves near national borders so that they can obtain redundant power from not just separate grids, but from separate geopolitical sources.

Higher redundancy levels required by a company will of invariably lead to higher prices. If one requires high availability backed by a service-level agreement (SLA), one can expect to pay more than another company with less demanding redundancy requirements.

Stay Tuned for Part 2 of The Challenges of Opening a Data Center

That’s it for part 1 of this post. In subsequent posts, we’ll take a look at some other factors to consider when moving into a data center such as network bandwidth, cooling, and security. We’ll take a look at what is involved in moving into a new data center (including stories from Backblaze’s experiences). We’ll also investigate what it takes to keep a data center running, and some of the new technologies and trends affecting data center design and use. You can discover all posts on our blog tagged with “Data Center” by following the link https://www.backblaze.com/blog/tag/data-center/.

The second part of this series on The Challenges of Opening a Data Center will be posted later this week. Use the Join button above to receive notification of future posts in this series.

The post The Challenges of Opening a Data Center — Part 1 appeared first on Backblaze Blog | Cloud Storage & Cloud Backup.

Jumping Air Gaps

Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2018/02/jumping_air_gap_2.html

Nice profile of Mordechai Guri, who researches a variety of clever ways to steal data over air-gapped computers.

Guri and his fellow Ben-Gurion researchers have shown, for instance, that it's possible to trick a fully offline computer into leaking data to another nearby device via the noise its internal fan generates, by changing air temperatures in patterns that the receiving computer can detect with thermal sensors, or even by blinking out a stream of information from a computer hard drive LED to the camera on a quadcopter drone hovering outside a nearby window. In new research published today, the Ben-Gurion team has even shown that they can pull data off a computer protected by not only an air gap, but also a Faraday cage designed to block all radio signals.

Here’s a page with all the research results.

BoingBoing post.

Astro Pi Mission Zero: your code is in space

Post Syndicated from David Honess original https://www.raspberrypi.org/blog/astro-pi-mission-zero-day/

Every school year, we run the European Astro Pi challenge to find the next generation of space scientists who will program two space-hardened Raspberry Pi units, called Astro Pis, living aboard the International Space Station.

Italian ESA Astronaut Paolo Nespoli with the Astro Pi units. Image credit ESA.

Astro Pi Mission Zero

The 2017–2018 challenge included the brand-new non-competitive Mission Zero, which guaranteed that participants could have their code run on the ISS for 30 seconds, provided they followed the rules. They would also get a certificate showing the exact time period during which their code ran in space.

Astro Pi Mission Zero logo

We asked participants to write a simple Python program to display a personalised message and the air temperature on the Astro Pi screen. No special hardware was needed, since all the code could be written in a web browser using the Sense HAT emulator developed in partnership with Trinket.

Scott McKenzie on Twitter

Students coding #astropi emulator to scroll a message to astronauts on @Raspberry_Pi in space this summer. Try it here: https://t.co/0KURq11X0L #Rm9Parents #CSforAll #ontariocodes

And now it’s time…

We received over 2500 entries for Mission Zero, and we’re excited to announce that tomorrow all entries with flight status will be run on the ISS…in SPAAACE!

There are 1771 Python programs with flight status, which will run back-to-back on Astro Pi VIS (Ed). The whole process will take about 14 hours. This means that everyone will get a timestamp showing 1 February, so we’re going to call this day Mission Zero Day!

Part of each team’s certificate will be a map, like the one below, showing the exact location of the ISS while the team’s code was running.

The grey line is the ISS orbital path, the red marker shows the ISS’s location when their code was running. Produced using Google Static Maps API.

The programs will be run in the same sequence in which we received them. For operational reasons, we can’t guarantee that they will run while the ISS flies over any particular location. However, if you have submitted an entry to Mission Zero, there is a chance that your code will run while the ISS is right overhead!

Go out and spot the station

Spotting the ISS is a great activity to do by yourself or with your students. The station looks like a very fast-moving star that crosses the sky in just a few minutes. If you know when and where to look, and it’s not cloudy, you literally can’t miss it.

Source Andreas Möller, Wikimedia Commons.

The ISS passes over most ground locations about twice a day. For it to be clearly visible though, you need darkness on the ground with sunlight on the ISS due to its altitude. There are a number of websites which can tell you when these visible passes occur, such as NASA’s Spot the Station. Each of the sites requires you to give your location so it can work out when visible passes will occur near you.

Visible ISS pass star chart from Heavens Above, on which familiar constellations such as the Plough (see label Ursa Major) can be seen.

A personal favourite of mine is Heavens Above. It’s slightly more fiddly to use than other sites, but it produces brilliant star charts that show you precisely where to look in the sky. This is how it works:

  1. Go to www.heavens-above.com
  2. To set your location, click on Unspecified in the top right-hand corner
  3. Enter your location (e.g. Cambridge, United Kingdom) into the text box and click Search
  4. The map should change to the correct location — scroll down and click Update
  5. You’ll be taken back to the homepage, but with your location showing at the top right
  6. Click on ISS in the Satellites section
  7. A table of dates will now show, which are the upcoming visible passes for your location
  8. Click on a row to view the star chart for that pass — the line is the path of the ISS, and the arrow shows direction of travel
  9. Be outside in cloudless weather at the start time, look towards the direction where the line begins, and hope the skies stay clear

If you go out and do this, then tweet some pictures to @raspberry_pi, @astro_pi, and @esa. Good luck!

More Astro Pi

Mission Zero certificates will be arriving in participants’ inboxes shortly. We would like to thank everyone who participated in Mission Zero this school year, and we hope that next time you’ll take it one step further and try Mission Space Lab.

Mission Zero and Mission Space Lab are two really exciting programmes that young people of all ages can take part in. If you would like to be notified when the next round of Astro Pi opens for registrations, sign up to our mailing list here.

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2017 Weather Station round-up

Post Syndicated from Richard Hayler original https://www.raspberrypi.org/blog/2017-weather-station/

As we head into 2018 and start looking forward to longer days in the Northern hemisphere, I thought I’d take a look back at last year’s weather using data from Raspberry Pi Oracle Weather Stations. One of the great things about the kit is that as well as uploading all its readings to the shared online Oracle database, it stores them locally on the Pi in a MySQL or MariaDB database. This means you can use the power of SQL queries coupled with Python code to do automatic data analysis.

Soggy Surrey

My Weather Station has only been installed since May, so I didn’t have a full 52 weeks of my own data to investigate. Still, my station recorded more than 70000 measurements. Living in England, the first thing I wanted to know was: which was the wettest month? Unsurprisingly, both in terms of average daily rainfall and total rainfall, the start of the summer period — exactly when I went on a staycation — was the soggiest:

What about the global Weather Station community?

Even soggier Bavaria

Here things get slightly trickier. Although we have a shiny Oracle database full of all participating schools’ sensor readings, some of the data needs careful interpretation. Many kits are used as part of the school curriculum and do not always record genuine outdoor conditions. Nevertheless, it appears that Adalbert Stifter Gymnasium in Bavaria, Germany, had an even wetter 2017 than my home did:


View larger map

Where the wind blows

The records Robert-Dannemann Schule in Westerstede, Germany, is a good example of data which was most likely collected while testing and investigating the weather station sensors, rather than in genuine external conditions. Unless this school’s Weather Station was transported to a planet which suffers from extreme hurricanes, it wasn’t actually subjected to wind speeds above 1000km/h in November. Dismissing these and all similarly suspect records, I decided to award the ‘Windiest location of the year’ prize to CEIP Noalla-Telleiro, Spain.


View larger map

This school is right on the coast, and is subject to some strong and squally weather systems.

Weather Station at CEIP Noalla - Telleiro

Weather Station at CEIP Noalla-Telleiro

They’ve mounted their wind vane and anemometer nice and high, so I can see how they were able to record such high wind velocities.

A couple of Weather Stations have recently been commissioned in equally exposed places — it will be interesting to see whether they will record even higher speeds during 2018.

Highs and lows

After careful analysis and a few disqualifications (a couple of Weather Stations in contention for this category were housed indoors), the ‘Hottest location’ award went to High School of Chalastra in Thessaloniki, Greece. There were a couple of Weather Stations (the one at The Marwadi Education Foundation in India, for example) that reported higher average temperatures than Chalastra’s 24.54 ºC. However, they had uploaded far fewer readings and their data coverage of 2017 was only partial.


View larger map

At the other end of the thermometer, the location with the coldest average temperature is École de la Rose Sauvage in Calgary, Canada, with a very chilly 9.9 ºC.

Ecole de la Rose sauvage Weather Station

Weather Station at École de la Rose Sauvage

I suspect this school has a good chance of retaining the title: their lowest 2017 temperature of -24 ºC is likely to be beaten in 2018 due to extreme weather currently bringing a freezing start to the year in that part of the world.


View larger map

Analyse your own Weather Station data

If you have an Oracle Raspberry Pi Weather Station and would like to perform an annual review of your local data, you can use this Python script as a starting point. It will display a monthly summary of the temperature and rainfall for 2017, and you should be able to customise the code to focus on other sensor data or on a particular time of year. We’d love to see your results, so please share your findings with [email protected], and we’ll send you some limited-edition Weather Station stickers.

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What is HAMR and How Does It Enable the High-Capacity Needs of the Future?

Post Syndicated from Andy Klein original https://www.backblaze.com/blog/hamr-hard-drives/

HAMR drive illustration

During Q4, Backblaze deployed 100 petabytes worth of Seagate hard drives to our data centers. The newly deployed Seagate 10 and 12 TB drives are doing well and will help us meet our near term storage needs, but we know we’re going to need more drives — with higher capacities. That’s why the success of new hard drive technologies like Heat-Assisted Magnetic Recording (HAMR) from Seagate are very relevant to us here at Backblaze and to the storage industry in general. In today’s guest post we are pleased to have Mark Re, CTO at Seagate, give us an insider’s look behind the hard drive curtain to tell us how Seagate engineers are developing the HAMR technology and making it market ready starting in late 2018.

What is HAMR and How Does It Enable the High-Capacity Needs of the Future?

Guest Blog Post by Mark Re, Seagate Senior Vice President and Chief Technology Officer

Earlier this year Seagate announced plans to make the first hard drives using Heat-Assisted Magnetic Recording, or HAMR, available by the end of 2018 in pilot volumes. Even as today’s market has embraced 10TB+ drives, the need for 20TB+ drives remains imperative in the relative near term. HAMR is the Seagate research team’s next major advance in hard drive technology.

HAMR is a technology that over time will enable a big increase in the amount of data that can be stored on a disk. A small laser is attached to a recording head, designed to heat a tiny spot on the disk where the data will be written. This allows a smaller bit cell to be written as either a 0 or a 1. The smaller bit cell size enables more bits to be crammed into a given surface area — increasing the areal density of data, and increasing drive capacity.

It sounds almost simple, but the science and engineering expertise required, the research, experimentation, lab development and product development to perfect this technology has been enormous. Below is an overview of the HAMR technology and you can dig into the details in our technical brief that provides a point-by-point rundown describing several key advances enabling the HAMR design.

As much time and resources as have been committed to developing HAMR, the need for its increased data density is indisputable. Demand for data storage keeps increasing. Businesses’ ability to manage and leverage more capacity is a competitive necessity, and IT spending on capacity continues to increase.

History of Increasing Storage Capacity

For the last 50 years areal density in the hard disk drive has been growing faster than Moore’s law, which is a very good thing. After all, customers from data centers and cloud service providers to creative professionals and game enthusiasts rarely go shopping looking for a hard drive just like the one they bought two years ago. The demands of increasing data on storage capacities inevitably increase, thus the technology constantly evolves.

According to the Advanced Storage Technology Consortium, HAMR will be the next significant storage technology innovation to increase the amount of storage in the area available to store data, also called the disk’s “areal density.” We believe this boost in areal density will help fuel hard drive product development and growth through the next decade.

Why do we Need to Develop Higher-Capacity Hard Drives? Can’t Current Technologies do the Job?

Why is HAMR’s increased data density so important?

Data has become critical to all aspects of human life, changing how we’re educated and entertained. It affects and informs the ways we experience each other and interact with businesses and the wider world. IDC research shows the datasphere — all the data generated by the world’s businesses and billions of consumer endpoints — will continue to double in size every two years. IDC forecasts that by 2025 the global datasphere will grow to 163 zettabytes (that is a trillion gigabytes). That’s ten times the 16.1 ZB of data generated in 2016. IDC cites five key trends intensifying the role of data in changing our world: embedded systems and the Internet of Things (IoT), instantly available mobile and real-time data, cognitive artificial intelligence (AI) systems, increased security data requirements, and critically, the evolution of data from playing a business background to playing a life-critical role.

Consumers use the cloud to manage everything from family photos and videos to data about their health and exercise routines. Real-time data created by connected devices — everything from Fitbit, Alexa and smart phones to home security systems, solar systems and autonomous cars — are fueling the emerging Data Age. On top of the obvious business and consumer data growth, our critical infrastructure like power grids, water systems, hospitals, road infrastructure and public transportation all demand and add to the growth of real-time data. Data is now a vital element in the smooth operation of all aspects of daily life.

All of this entails a significant infrastructure cost behind the scenes with the insatiable, global appetite for data storage. While a variety of storage technologies will continue to advance in data density (Seagate announced the first 60TB 3.5-inch SSD unit for example), high-capacity hard drives serve as the primary foundational core of our interconnected, cloud and IoT-based dependence on data.

HAMR Hard Drive Technology

Seagate has been working on heat assisted magnetic recording (HAMR) in one form or another since the late 1990s. During this time we’ve made many breakthroughs in making reliable near field transducers, special high capacity HAMR media, and figuring out a way to put a laser on each and every head that is no larger than a grain of salt.

The development of HAMR has required Seagate to consider and overcome a myriad of scientific and technical challenges including new kinds of magnetic media, nano-plasmonic device design and fabrication, laser integration, high-temperature head-disk interactions, and thermal regulation.

A typical hard drive inside any computer or server contains one or more rigid disks coated with a magnetically sensitive film consisting of tiny magnetic grains. Data is recorded when a magnetic write-head flies just above the spinning disk; the write head rapidly flips the magnetization of one magnetic region of grains so that its magnetic pole points up or down, to encode a 1 or a 0 in binary code.

Increasing the amount of data you can store on a disk requires cramming magnetic regions closer together, which means the grains need to be smaller so they won’t interfere with each other.

Heat Assisted Magnetic Recording (HAMR) is the next step to enable us to increase the density of grains — or bit density. Current projections are that HAMR can achieve 5 Tbpsi (Terabits per square inch) on conventional HAMR media, and in the future will be able to achieve 10 Tbpsi or higher with bit patterned media (in which discrete dots are predefined on the media in regular, efficient, very dense patterns). These technologies will enable hard drives with capacities higher than 100 TB before 2030.

The major problem with packing bits so closely together is that if you do that on conventional magnetic media, the bits (and the data they represent) become thermally unstable, and may flip. So, to make the grains maintain their stability — their ability to store bits over a long period of time — we need to develop a recording media that has higher coercivity. That means it’s magnetically more stable during storage, but it is more difficult to change the magnetic characteristics of the media when writing (harder to flip a grain from a 0 to a 1 or vice versa).

That’s why HAMR’s first key hardware advance required developing a new recording media that keeps bits stable — using high anisotropy (or “hard”) magnetic materials such as iron-platinum alloy (FePt), which resist magnetic change at normal temperatures. Over years of HAMR development, Seagate researchers have tested and proven out a variety of FePt granular media films, with varying alloy composition and chemical ordering.

In fact the new media is so “hard” that conventional recording heads won’t be able to flip the bits, or write new data, under normal temperatures. If you add heat to the tiny spot on which you want to write data, you can make the media’s coercive field lower than the magnetic field provided by the recording head — in other words, enable the write head to flip that bit.

So, a challenge with HAMR has been to replace conventional perpendicular magnetic recording (PMR), in which the write head operates at room temperature, with a write technology that heats the thin film recording medium on the disk platter to temperatures above 400 °C. The basic principle is to heat a tiny region of several magnetic grains for a very short time (~1 nanoseconds) to a temperature high enough to make the media’s coercive field lower than the write head’s magnetic field. Immediately after the heat pulse, the region quickly cools down and the bit’s magnetic orientation is frozen in place.

Applying this dynamic nano-heating is where HAMR’s famous “laser” comes in. A plasmonic near-field transducer (NFT) has been integrated into the recording head, to heat the media and enable magnetic change at a specific point. Plasmonic NFTs are used to focus and confine light energy to regions smaller than the wavelength of light. This enables us to heat an extremely small region, measured in nanometers, on the disk media to reduce its magnetic coercivity,

Moving HAMR Forward

HAMR write head

As always in advanced engineering, the devil — or many devils — is in the details. As noted earlier, our technical brief provides a point-by-point short illustrated summary of HAMR’s key changes.

Although hard work remains, we believe this technology is nearly ready for commercialization. Seagate has the best engineers in the world working towards a goal of a 20 Terabyte drive by 2019. We hope we’ve given you a glimpse into the amount of engineering that goes into a hard drive. Keeping up with the world’s insatiable appetite to create, capture, store, secure, manage, analyze, rapidly access and share data is a challenge we work on every day.

With thousands of HAMR drives already being made in our manufacturing facilities, our internal and external supply chain is solidly in place, and volume manufacturing tools are online. This year we began shipping initial units for customer tests, and production units will ship to key customers by the end of 2018. Prepare for breakthrough capacities.

The post What is HAMR and How Does It Enable the High-Capacity Needs of the Future? appeared first on Backblaze Blog | Cloud Storage & Cloud Backup.

Presenting AWS IoT Analytics: Delivering IoT Analytics at Scale and Faster than Ever Before

Post Syndicated from Tara Walker original https://aws.amazon.com/blogs/aws/launch-presenting-aws-iot-analytics/

One of the technology areas I thoroughly enjoy is the Internet of Things (IoT). Even as a child I used to infuriate my parents by taking apart the toys they would purchase for me to see how they worked and if I could somehow put them back together. It seems somehow I was destined to end up the tough and ever-changing world of technology. Therefore, it’s no wonder that I am really enjoying learning and tinkering with IoT devices and technologies. It combines my love of development and software engineering with my curiosity around circuits, controllers, and other facets of the electrical engineering discipline; even though an electrical engineer I can not claim to be.

Despite all of the information that is collected by the deployment of IoT devices and solutions, I honestly never really thought about the need to analyze, search, and process this data until I came up against a scenario where it became of the utmost importance to be able to search and query through loads of sensory data for an anomaly occurrence. Of course, I understood the importance of analytics for businesses to make accurate decisions and predictions to drive the organization’s direction. But it didn’t occur to me initially, how important it was to make analytics an integral part of my IoT solutions. Well, I learned my lesson just in time because this re:Invent a service is launching to make it easier for anyone to process and analyze IoT messages and device data.

 

Hello, AWS IoT Analytics!  AWS IoT Analytics is a fully managed service of AWS IoT that provides advanced data analysis of data collected from your IoT devices.  With the AWS IoT Analytics service, you can process messages, gather and store large amounts of device data, as well as, query your data. Also, the new AWS IoT Analytics service feature integrates with Amazon Quicksight for visualization of your data and brings the power of machine learning through integration with Jupyter Notebooks.

Benefits of AWS IoT Analytics

  • Helps with predictive analysis of data by providing access to pre-built analytical functions
  • Provides ability to visualize analytical output from service
  • Provides tools to clean up data
  • Can help identify patterns in the gathered data

Be In the Know: IoT Analytics Concepts

  • Channel: archives the raw, unprocessed messages and collects data from MQTT topics.
  • Pipeline: consumes messages from channels and allows message processing.
    • Activities: perform transformations on your messages including filtering attributes and invoking lambda functions advanced processing.
  • Data Store: Used as a queryable repository for processed messages. Provide ability to have multiple datastores for messages coming from different devices or locations or filtered by message attributes.
  • Data Set: Data retrieval view from a data store, can be generated by a recurring schedule. 

Getting Started with AWS IoT Analytics

First, I’ll create a channel to receive incoming messages.  This channel can be used to ingest data sent to the channel via MQTT or messages directed from the Rules Engine. To create a channel, I’ll select the Channels menu option and then click the Create a channel button.

I’ll name my channel, TaraIoTAnalyticsID and give the Channel a MQTT topic filter of Temperature. To complete the creation of my channel, I will click the Create Channel button.

Now that I have my Channel created, I need to create a Data Store to receive and store the messages received on the Channel from my IoT device. Remember you can set up multiple Data Stores for more complex solution needs, but I’ll just create one Data Store for my example. I’ll select Data Stores from menu panel and click Create a data store.

 

I’ll name my Data Store, TaraDataStoreID, and once I click the Create the data store button and I would have successfully set up a Data Store to house messages coming from my Channel.

Now that I have my Channel and my Data Store, I will need to connect the two using a Pipeline. I’ll create a simple pipeline that just connects my Channel and Data Store, but you can create a more robust pipeline to process and filter messages by adding Pipeline activities like a Lambda activity.

To create a pipeline, I’ll select the Pipelines menu option and then click the Create a pipeline button.

I will not add an Attribute for this pipeline. So I will click Next button.

As we discussed there are additional pipeline activities that I can add to my pipeline for the processing and transformation of messages but I will keep my first pipeline simple and hit the Next button.

The final step in creating my pipeline is for me to select my previously created Data Store and click Create Pipeline.

All that is left for me to take advantage of the AWS IoT Analytics service is to create an IoT rule that sends data to an AWS IoT Analytics channel.  Wow, that was a super easy process to set up analytics for IoT devices.

If I wanted to create a Data Set as a result of queries run against my data for visualization with Amazon Quicksight or integrate with Jupyter Notebooks to perform more advanced analytical functions, I can choose the Analyze menu option to bring up the screens to create data sets and access the Juypter Notebook instances.

Summary

As you can see, it was a very simple process to set up the advanced data analysis for AWS IoT. With AWS IoT Analytics, you have the ability to collect, visualize, process, query and store large amounts of data generated from your AWS IoT connected device. Additionally, you can access the AWS IoT Analytics service in a myriad of different ways; the AWS Command Line Interface (AWS CLI), the AWS IoT API, language-specific AWS SDKs, and AWS IoT Device SDKs.

AWS IoT Analytics is available today for you to dig into the analysis of your IoT data. To learn more about AWS IoT and AWS IoT Analytics go to the AWS IoT Analytics product page and/or the AWS IoT documentation.

Tara

In the Works – AWS IoT Device Defender – Secure Your IoT Fleet

Post Syndicated from Jeff Barr original https://aws.amazon.com/blogs/aws/in-the-works-aws-sepio-secure-your-iot-fleet/

Scale takes on a whole new meaning when it comes to IoT. Last year I was lucky enough to tour a gigantic factory that had, on average, one environment sensor per square meter. The sensors measured temperature, humidity, and air purity several times per second, and served as an early warning system for contaminants. I’ve heard customers express interest in deploying IoT-enabled consumer devices in the millions or tens of millions.

With powerful, long-lived devices deployed in a geographically distributed fashion, managing security challenges is crucial. However, the limited amount of local compute power and memory can sometimes limit the ability to use encryption and other forms of data protection.

To address these challenges and to allow our customers to confidently deploy IoT devices at scale, we are working on IoT Device Defender. While the details might change before release, AWS IoT Device Defender is designed to offer these benefits:

Continuous AuditingAWS IoT Device Defender monitors the policies related to your devices to ensure that the desired security settings are in place. It looks for drifts away from best practices and supports custom audit rules so that you can check for conditions that are specific to your deployment. For example, you could check to see if a compromised device has subscribed to sensor data from another device. You can run audits on a schedule or on an as-needed basis.

Real-Time Detection and AlertingAWS IoT Device Defender looks for and quickly alerts you to unusual behavior that could be coming from a compromised device. It does this by monitoring the behavior of similar devices over time, looking for unauthorized access attempts, changes in connection patterns, and changes in traffic patterns (either inbound or outbound).

Fast Investigation and Mitigation – In the event that you get an alert that something unusual is happening, AWS IoT Device Defender gives you the tools, including contextual information, to help you to investigate and mitigate the problem. Device information, device statistics, diagnostic logs, and previous alerts are all at your fingertips. You have the option to reboot the device, revoke its permissions, reset it to factory defaults, or push a security fix.

Stay Tuned
I’ll have more info (and a hands-on post) as soon as possible, so stay tuned!

Jeff;

Ultimate 3D printer control with OctoPrint

Post Syndicated from Alex Bate original https://www.raspberrypi.org/blog/octoprint/

Control and monitor your 3D printer remotely with a Raspberry Pi and OctoPrint.

Timelapse of OctoPrint Ornament

Printed on a bq Witbox STL file can be found here: http://www.thingiverse.com/thing:191635 OctoPrint is located here: http://www.octoprint.org

3D printing

Whether you have a 3D printer at home or use one at your school or local makerspace, it’s fair to assume you’ve had a failed print or two in your time. Filament knotting or running out, your print peeling away from the print bed — these are common issues for all 3D printing enthusiasts, and they can be costly if they’re discovered too late.

OctoPrint

OctoPrint is a free open-source software, created and maintained by Gina Häußge, that performs a multitude of useful 3D printing–related tasks, including remote control of your printer, live video, and data collection.

The OctoPrint logo

Control and monitoring

To control the print process, use OctoPrint on a Raspberry Pi connected to your 3D printer. First, ensure a safe uninterrupted run by using the software to restrict who can access the printer. Then, before starting your print, use the web app to work on your STL file. The app also allows you to reposition the print head at any time, as well as pause or stop printing if needed.

Live video streaming

Since OctoPrint can stream video of your print as it happens, you can watch out for any faults that may require you to abort and restart. Proud of your print? Record the entire process from start to finish and upload the time-lapse video to your favourite social media platform.

OctoPrint software graphic user interface screenshot

Data capture

Octoprint records real-time data, such as the temperature, giving you another way to monitor your print to ensure a smooth, uninterrupted process. Moreover, the records will help with troubleshooting if there is a problem.

OctoPrint software graphic user interface screenshot

Print the Millenium Falcon

OK, you can print anything you like. However, this design definitely caught our eye this week.

3D-Printed Fillenium Malcon (Timelapse)

This is a Timelapse of my biggest print project so far on my own designed/built printer. It’s 500x170x700(mm) and weights 3 Kilograms of Filament.

You can support the work of Gina and OctoPrint by visiting her Patreon account and following OctoPrint on Twitter, Facebook, or G+. And if you’ve set up a Raspberry Pi to run OctoPrint, or you’ve created some cool Pi-inspired 3D prints, make sure to share them with us on our own social media channels.

The post Ultimate 3D printer control with OctoPrint appeared first on Raspberry Pi.