Enabling and Advancing Human and Probabilistic Context Awareness for Smart Facilities and Elder Care

However, we cannot always assume a person could carry a tag, i.e. intrusion detection, or hostage situation. I starts looking into device-free localization. In simple terms, rather than locating a tag, sensors would be deployed to detect changes in the environment and convert them into an image using RTI. Prof. Patwari and his previous students have done a lot of research on this specific topic already. However, we found that in RTI, small scale fading greatly affects the localization accuracy. In other words, certain placement of sensors could improve accuracy. Therefore, we built this sensor as you can see with a sail winch servo motor and standard zigbee sensor node, CC2531. With this, we found that we could adaptively change sensor placement and optimize the network for better localization performance, as much as 32% less in localization error.

In this joint work, I designed and implemented the hardware and firmware to automatically moved sensors in order to optimize the fading condition of the channels. I was also apart of deployment and testing of the full localization system.

[Website, GitHub]