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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 […]
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 […]
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 […]
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. Also read this Fortune.com article about how […]
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 […]
via Green Building Elements | From brick and mortar shops to city planning, we cover sustainable trends in construction, renovation, and more.. 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 […]
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 […]
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 […]
Running Kafka for a streaming collection service can feel somewhat opaque at times, this is why I was thrilled to find the Kafka Web Console project on Github yesterday. This Scala application can be easily downloaded and installed with a couple steps. An included web server can then be launched to serve it up quickly. Here’s […]
Between classic business transactions and social interactions and machine-generated observations, the digital data tap has been turned on and it will never be turned off. The flow of data is everlasting. Which is why you see a lot of things in the loop around real time frameworks and streaming frameworks. – Mike Hoskins, CTO Actian […]
The OSX “open” command line tool is very useful. Use it to launch a URL or point to a folder and the web browser or Finder pops up automatically. But what about when you want to launch a particular app to handle a resource you provide? It can do that as well. Easily. In this example […]
Kibana dashboards, from the Elasticsearch project, can help you visualise activity and incidents in log files. Here I show 3 different types of use cases for dashboards and how each can be used to answer different questions depending on the person. Video and details follow.
[UPDATE: Check out the Kafka Web Console that allows you to manage topics and see traffic going through your topics – all in a browser!] When you’re pushing data into a Kafka topic, it’s always helpful to monitor the traffic using a simple Kafka consumer script. Here’s a simple script I’ve been using that […]
Graph analysis is all about finding relationships. In this post I show how to compute graph density (a ratio of how well connected relationships in a graph are) using a Cypher query with Neo4j. This is a follow up to the earlier post: SPARQL Query for Graph Density Analysis. Installing Neo4j Graph Database In this example we launch Neo4j and […]
Code snippet: SPARQL Query Graph Density I’m testing out sharing SPARQL code snippets using Github Gist features. I’ll be adding more as I work through more graph-specific examples using SPARQLverse, but here is my first one: View the code on Gist. Ideally we’d have a common landing place for building up a library of these […]
In preparation for a post about doing graph analytics in Neo4j (paralleling SPARQLverse from this earlier post), I had to learn to load text/CSV data into Neo. This post just shows the steps I took to load nodes and then establish edges/relationships in the database. My head hurt trying to find a simple example of […]
Graph analytics – is it just hype or is it technology that has come of age? Mike Hoskins, CTO of Actian sums it up well in this article from InfoWorld: “One area where graph analytics particularly earns its stripes is in data discovery. While most of the discussion around big data has centered on how to […]
I’ve been spending a lot of time this past year running queries against the open source SPARQLverse graph analytic engine. It’s amazing how simple some queries can look and yet how much work is being done behind the scenes. My current project requires building up a set of query examples that allow typical kinds of graph/network […]
[UPDATE: Check out the Kafka Web Console to more easily administer your Kafka topics] This week I’ve been working with the Kafka messaging system in a project. Basic C# Methods for Kafka Producer To publish to Kafka I built a C# app that uses the Kafka4n libraries – it doesn’t get much simpler than this: using Kafka.Client; Connector […]
I pulled this visualization of my LinkedIn social graph together in just a few minutes while working through a tutorial. What about other social networks? Give me your input…
