This issue is a follow up to #4734 where we discuss the foundation of an open platform that measures things and people and events.
The Internet of Things is coming to Planet Earth within the coming years. Along with these devices and things and sensors, a lot of new data will be collected. Vendors will often provide basic software to collect the data or they will sell this service (with privacy).
The cost of sensors have gone down just like the cost of bandwith and processing power. Wi-fi coverage is now ubiquitous in many homes and places.
The goal of this issue is to discuss ideas on how together build an open platform that lets you measure the Internet of Things.
-> have you got ideas or suggestions about tracking the Internet of Things? please comment on this issue, let's enjoy a public brainstorming session on this important topic.
btw: I'm not yet convinced that it's a good idea to connect many more things to the Internet... when such objects bring medical or well-being benefits it is a strong bonus. but some of the IoT stuff is going and will continue to go too far. these objects and things will often generate loads of interesting data. we must be able to keep all our data in our own silo. this is our part to play in keeping the web decentralised. see as well this RWW article that lists some of the other challenges of IoT Why the Internet of Things is still rockblocked (tag line: Its potential is huge; so are the obstacles.)
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.