SCALECycle and Crowd Augmented Urban Sensing Qiuxi Zhu

Background Pollution is a severe problem in many densely populated urban areas. Pollution monitoring provides guidelines for residents and feedback to decision makers. Internet of Things (IoT) helps build fine-grained (high- resolution) pollution maps for cities. This include deployed systems and mobile devices owned by crowd. We anticipate a large number of IoT devices will participate in monitoring multiple types of pollutions in the next years. The growing crowd participant population, if not coordinated appropriately, can generate redundant data, which consumes resources but contributes little. Picture: Beijing, Dec 25, 2015 http://news.sohu.com/20151225/n432582431.shtml

SCALECycle Mobile sensing SCALE multi-sensor box mounted on a bike, with GPS, Wi-Fi, battery Multiple sensors Tested in two testbeds (UCI campus and Victory Court Senior Apartments in Rockville, MD) Collected Wi-Fi RSSI/quality and air quality data.

Multi-timescale scheduling problem Region of interest is divided into cells. There are multiple data types we collect, and each node has a subset of these sensors. Each sensor can be activated individually and generate data at certain rate. Max data coverage and limit data size.

Multi-timescale scheduling problem (cont.) Problem formulation Multi-objective optimization Approach In each time frame, use estimated location to plan for next n' frames. Adjust plan in future for uncertainty in mobility. Measurement study Data (sensor) types Temporal and spatial validity of readings Data generation model (sample size, interval) Nodes Mobility model Discretization Size of cells and length of time frames

Possible directions for projects Pick an application scenario and build SCALECycle mobile nodes with appropriate sensors. Data management backend for SCALE and SCALECycle and appropriate front end for showcase. Improve an existing simulator or write your own simulator to create a simulation platform for large-scale crowd augmented sensing studies. …

SCALECycle and Crowd Augmented Urban Sensing Thank you! SCALE project home – http://scale.ics.uci.edu/ For your reference Q. Zhu, et al. “Upload Planning for Mobile Data Collection in Smart Community Internet-of-Things Deployments,” in SMARTCOMP ‘16. M. Y. S. Uddin, et al. “The SCALE2 Multi-network Architecture for IoT-based Resilient Communities, ” in SMARTCOMP ‘16. K. Benson, et al. “SCALE: Safe community awareness and alerting leveraging the internet of things,” IEEE Communications Magazine, Dec. 2015.