• Stats: it is expected that there will be 25+ billion devices connected to the Internet in 2020: Wow! this is quite incredible...
• Maybe we need an Arduino client and/or Raspberry Pi client to measure embedded tools and objects and things with Piwik?
• See also TRUSTE IoT infographic http://www.slideshare.net/trusteprivacyseals/truste-internet-of-things-iot-infographic-us-edition

Good opinion paper from the independent European advisory body on data protection and privacy about the Internet of Things & privacy: source

Privacy and data protection challenges related to the Internet of things

1. Lack of control and information asymmetry
2. Quality of the user’s consent
3. Inferences derived from data and repurposing of original processing
4. Intrusive bringing out of behaviour patterns and profi
5. Limitations on the possibility to remain anonymous when using serv
6. Security risks: security vs. efficiency

Piwik used for IoT analytics would help solve many of these privacy challenges!

interesting article: Get To Know The Four Types Of Data In The Internet Of Things

The Five Kinds Of Big Data

Status Data

Are the air compressors for the cold storage unit working? Did one just suddenly drop in performance? Status data essentially providers consumers and or businesses with an ongoing EKG of the world’s things.

Status data is the most prevalent, and most basic, type of IoT data. Virtually everything will generate data like this as a baseline. In many markets, status data will be mostly used as raw material for more complex analyses, but in many markets it will have a significant value of its own.

Look at what Streetline had done for parking spots. The company has created a system that notifies subscribers about open parking spaces. Sure, the long-term data helps city planners, but to most consumers the immediate status data is the most important thing.

Location Data

Where is my product? Did it make it to its destination? Location is a logical extension of GPS. GPS is great, but it doesn’t work well indoors, in crowded spaces or in rapidly changing environments. Someone trying to track pallets and robotic forklifts will want real-time information.

Agriculture, which could become an early IoT market, will make extensive use of location data because owners have to track equipment across huge geographical areas. While we’ve already seen the debut of consumer products so people can locate their keys, a larger markets exists for serving commercial and industrial customers, particularly where there are numerous assets to track, few employees, and need to track things in real, and near-real, time. Developing the Foursquare for paint warehouses is a huge opportunity.

Automation Data

Consumers are rightly skeptical about automation. You don’t want to be stuck in a dimly lit office or a chilly hotel room because some building management system care more about saving a few dollars than your comfort. Automation also creates security issues.

Nonetheless, automation is inevitable. No one is going to sit with their finger on the thermostat to save $4.75. Likewise, lighting systems that depend on human interaction fail. (Some smart-lighting manufacturers want to use their sensor data to tell store managers when new checkout lines need to be opened.) The challenge will revolve around carving out applications and rules of conduct.

Actionable Data

Think of this as status data with a follow-up plan. Buildings use 73% of the electricity in the country and a good portion—up to 30%, according to the EPA—is wasted. Why? Energy is a secondary issue for most building owners. They want to fix it but worry that the cost, time and headaches will outweigh the benefits.

There are two ways around this problem: automation (see above) that can change the immediate state of a system, and persuasion that can get people to change their behavior or make long term investments. Opower has helped pioneer a solution to the persuasion problem by showing consumers and businesses how they compare to their neighbors along with data. According to their own studies, persuasion data can cut energy consumption by 2 to 3 percent.