Decked out in new running shirts and scarves, 52°North took advantage of the cool weather and a hiatus in the rain to participate in this year’s Firmenlauf this past Saturday.
Increased support for Sensor Web standards
With the advent of low-cost, low-bandwidth and low-power IoT sensors, new requirements for data handling have arisen. The OGC SensorThings API (STA) was developed to accompany those new requirements and integrate those new sensors into the Sensor Web. It “[…] provides an open, geospatial-enabled and unified way to interconnect the Internet of Things (IoT) devices, data, and applications over the Web” (Preface to the OGC SensorThings API Part 1: Sensing). The main focus of this development is to find a solution for the heavy restraints on available resources. The STA therefore defines a lightweight REST-API, as well as an MQTT binding for easy retrieval and storage of Sensor Data with a minimal overhead. The “SensorThings API Part 1: Sensing” was officially adopted as an OGC Standard in late 2016, the “SensorThings API Part 2: Tasking” is currently under development.
This year’s Student Innovation Challenge addresses the topic of analyzing sensor data in the Sensor Web and generating higher level information products. My research topic draws inspiration from smart city applications. To be more specific, IoT sensor web technologies and 3D city models play significant roles in building the smart city. I argued that most of the existing solutions to integrating 3D city models and sensor observations are usually customized and lack interoperability. Therefore, in order to improve the interoperability of smart city models, I conclude that the integration of the IoT sensor service and the 3D city model have to be based on open standards.
Currently, the Android application for enviroCar can record tracks only when it is connected to the OBD-II adapter through Bluetooth. The enviroCar app will be of no use to the user, if he/she does not have a working OBD-II adapter or if Bluetooth is not working on the user’s mobile phone. This limits the usage of the app to a great extent. The main goal of this project is to add plain GPS-based recording of a track to the enviroCar Android application. This will increase the usability of the enviroCar app and simultaneously increase the collection of data on the enviroCar server. It is also equally important to automate the GPS-based track, for which Activity Recognition features can be used.