Mobile plus in-situ setup for IoT Leverage the advantages of in-situ IoT deployments and mobile devices! In-situ IoT deployments Mobile devices Large-num. low-cost dev. Real-time awareness and alerting services & apps Prior knowledge High dependency on community infrastructure On-demand deployment Extended coverage of sensing & data collection Reduced dependency of infrastructure Mobile agents & objects

Smart building fire scenario Normal operation Fire operation In-situ nodes in smart building IoT deployments Temperature and humidity Carbon dioxide and explosive gas Occupancy and presence Energy profile Wi-Fi connectivity Security (cameras) - Emergencies (events) Mobile devices carried by firefighters On-demand crowdsourcing Vitals DMG Calibration of sensors on in-situ nodes Data collection from in-situ nodes

Sensor calibration in IoT systems Crowd sensors from diff. vendors have diff. response to the same phenomenon. E.g. noise sensing with microphones on phones necessitates calibration. Sensors degrade and drift over time. E.g. MQ family gas sensors on our SCALE boxes need periodical calibration. In event detection systems, environmental changes affect accuracy of detection. The event detection process needs to be (re-)calibrated.

Planned multi-sensor calibration In-situ sensors on deployed multi-sensor boxes in the smart building need occasional calibration. Calibration is done by comparing sensor reading series with that from reference sensors carried by trained personnel, e.g. firefighters. Different types of sensors have different requirements on calibration period and accuracy. Building map is represented by a directed graph, the weights on edges denoting the cost (e.g. time/distance) of movement. At higher level, we determine which sensors need to be calibrated in each iteration (run), optimizing with the tradeoff between calibration workload and overall accuracy. At lower level, in each iteration, we plan the paths for mobile agents to minimize the total time/distance travelled by all agents.