2018/09/28 by Shiva R. Iyer, Soumie Kumar, Iyer, Shiva R. +7
Computer Science · Engineering · Environmental Science · #Air Quality Monitoring and Forecasting #Bluetooth and Wireless Communication Technologies #FOS: Computer and information sciences #Indoor and Outdoor Localization Technologies #Mobile Crowdsensing and Crowdsourcing #Networking and Internet Architecture (cs.NI)
paper · pdf · doi:10.48550/arxiv.1809.11120
openalex publication_date 2018/09/28 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
This vision paper presents the case for MUSIC, a programmable framework for\nbuilding distributed mobile IoT applications for urban sensing. The Mobile\nUrban Sensing, Inference and Control (MUSIC) framework is contextualized for\nscenarios where a distributed collection of static or mobile sensors\ncollectively achieve an urban sensing task. The MUSIC platform is designed for\nurban-centric sensing applications such as location sensing on mobile phones\nfor road traffic monitoring, air quality sensing and urban quality monitoring\nusing remote cameras. This programmable system, at a high level, consists of\nseveral small sensors placed throughout a city on mobile vehicles and a\ncentralized controller that makes decisions on sensing in order to achieve\ncertain well-defined objectives such as improving spatial coverage of sensing\nand detection of hotspots. The system is programmable in that our framework\nallows one to create custom smart systems by writing custom control logic for\nsensing. Our contributions are two-fold -- a backend software stack to enable\ncentralized control of distributed devices and programmability, and algorithms\nfor intelligent control in the presence of practical power and network\nconstraints. We briefly present three different urban sensing applications\nbuilt on top of the MUSIC stack.\n