Would love to hear how you partition your spatial data..
As data volumes grow, so does your need to understand how to partition your data. Until you understand this distributed storage concept, you will be unable to choose the best approach for the job. This post gives an introductory explanation of partitioning and you will see why it is integral to the Hadoop Distributed File System (HDFS) increasingly used in modern big data architectures….
I dug up one of my oldest blog posts from about 7 years ago. In the post, I show how I had connected my Garmin eTrex GPS receiver to an Arduino board and used it to control a camera in a desktop application.
After pumping the data into the Arduino, I parsed the raw GPS data coming from the eTrex and streamed it out to a Python app on the desktop, via a serial port. I was using the output to position a virtual camera in the OSSIMPlanet platform by formatting XML in Python and sending it to a listener built into the OSSIMPlanet app. (OSSIMPlanet is a sort of pre-Google Earth, Google Earth on steroids product.)
I haven’t used it for years, but thought some of the methods from this old post may still apply if you have an Arduino + GPS or Arduino -> Python streaming requirement. Enjoy the flashback – I know it’s inspired me to pick up a new Arduino to continue where I left off.
GPS Controls OSSIMPlanet-With OSSIMPlanet’s nifty camera control and listener functionality, as demonstrated in my last post, you’ve got so many neat opportunities. A couple nights ago I got a basic GPS NMEA parser working. Here’s a pic of the ultra-professional connection method I use to hook it to my arduino board 🙂 Oops, just realised that the picture … Continue reading GPS Controls OSSIMPlanet
Recently I started an Internet of Things series on my experiences installing, using and analysing data from a smart electrical meter. This included a BC Hydro smart meter, Eagle monitoring gateway from rainforest automation, and a cloud-based analytics service from Bidgely.
I’ve collated all the posts on the topic for you below. More will be added as I write them. Enjoy!
After a week of collecting smart meter readings, I’m now ready to show results in a cloud-based energy monitor system – Bidgely – complete with graphs showing readings, cost and machine learning results breaking down my usage by appliance.
This is part 4 of a series of posts about the Internet of Things applied to Home Energy Monitoring. I have a Smart Meter from BC Hydro, an Eagle energy monitor and various cloud apps helping me understand it all.
Working in the big data and analytics space, I’m always interested in parts of the Internet of Things (IoT) that will produce more data, require more backend systems, and help users/customers get on with their day better.
The past week has shown a few interesting announcements relating to Internet of Things topics. Here are just a few that jumped out to me, either because they inspired me or because I was left wondering what it would really mean.
TL;DR? Summary: While IBM is “getting started” (oops, I meant “getting serious”) and Facebook has big plans to “take over”, Amazon comes out with a consumer focused solution.
I like this concept: “Just press and never run out”. It’s the Amazon Dash Button: http://amazon.com/… – intended to be stuck onto appliances, basically retrofitting ones that don’t have them built in (in the future). Pressing a button orders refills of products, just like Amazon one click ordering online.
The Eagle energy monitor from Rainforest Automation is a very handy device. It reads the wireless signal from my electricity meter and makes it available through a web interface – both a graphical environment and a RESTful API. In this post we look at the standard graphical screens and the data download option. Next time we’ll look at the RESTful API for programmers to use.
This is part 3 of a series of posts about the Internet of Things applied to Home Energy Monitoring.
This definitely sounds promising, anyone have experience running a similar setup?
A small company, SpinRay Energy, has announced the production of a new UL listed, grid-tied solar power system that couldn’t be easier to install. Plug-in solar power equipment may be a game changer in the arena of small residential solar power.
I see two scenarios for those in rental environments – hanging something from windows or setting up on a porch. Ultimately I guess the efficacy will be limited by size availability and cost, but size issues could be minimised if it were possible to hang PV systems in some manner without needing to screw things down into exterior walls.
Just a thought – you tried anything like this? Share any links to your favourite portable, yet substantial, systems.
Energy monitoring isn’t only about knowing what’s happening right now, but also understanding what happened historically. Often that includes knowing not just what was happening but also when and why. Enter cloud services for energy monitoring. They range from simple charts and graphs to predicting your usage over time – essentially storing, analysing and enriching your raw data.
In this post I review two cloud services that I’ve tried so far and show you what you get from them. Continue reading IoT Day 2: Cloud Services for Energy Monitoring
In my next series of blog posts we explore an Internet of Things topic – Home energy monitoring – from a first person perspective. Join me as I install, use and hack a monitor (and related cloud services) in my new home.
This is part 1 of a series of posts about the Internet of Things applied to Home Energy Monitoring.