If you have a camera to detect burglars, an alarm system to detect opening doors, and a smoke detector to alert you in case of fire, wouldn’t it be nice if all these systems could be presented to you through one simple app? If you already have an integrated system like that, you probably bought all of the components at the same supplier. Adding third-party or Do-It-Yourself (DIY) sensors, or combining the data with other data sources, such as weather stations or the GPS-position of your mobile phone, is probably hard or impossible. Options to combine the data, however, would enable you to make your systems really smart…
To allow you to connect any type of sensor you wish, we are developing an open source Application Programming Interface (API). Any hobbyist or programmer can use it to connect his of her own device to the SCCSS-sensing platform. From there, the data may be presented in Cluey or WildCAT, or exported to CSV, XML or JSON, for further analysis.
Low-cost Smart Computer Vision Camera
A first trial project has been adopted by 4 students of Technasium Keizer Karel College Amsterdam. Noah, Robin, Celio and Dimme have the ambition to turn a standard webcam into a low-cost Smart Computer Vision Camera. That’s a camera which does not just take pictures, but which can be trained to takes pictures only when a person walks along, or a dog, tiger, elephant, or whatever else it has been trained for. Once the object of interest has been detected, a small image is created and sent to the Cluey-app.
A tough task, involving the mastering of Open Source Computer Vision software on a Raspberry Pi, Python programming, a little engineering, and lots of endurance, fun and enthusiasm!
Noah, Robin, Celio and Dimme expect to finish the project this summer. They will publish the source code and the “How to” in GitHub, thus making it available to the public for free.
The first results are looking good!
Screen print: Noah captured by the team’s engineering masterpiece, the low cost Smart Computer Vision Camera!