The Case for MUSIC: A Programmable IoT Framework for Mobile Urban Sensing Applications

TL;DR

MUSIC is a programmable framework designed for distributed mobile IoT urban sensing applications, enabling customizable control logic and intelligent management of sensors for tasks like traffic and air quality monitoring.

Contribution

The paper introduces a backend software stack and algorithms for centralized control and programmability of distributed urban sensors, addressing power and network constraints.

Findings

Successfully built three urban sensing applications on MUSIC

Demonstrated improved spatial coverage and hotspot detection

Enabled flexible, programmable control of mobile IoT sensors

Abstract

This vision paper presents the case for MUSIC, a programmable framework for building distributed mobile IoT applications for urban sensing. The Mobile Urban Sensing, Inference and Control (MUSIC) framework is contextualized for scenarios where a distributed collection of static or mobile sensors collectively achieve an urban sensing task. The MUSIC platform is designed for urban-centric sensing applications such as location sensing on mobile phones for road traffic monitoring, air quality sensing and urban quality monitoring using remote cameras. This programmable system, at a high level, consists of several small sensors placed throughout a city on mobile vehicles and a centralized controller that makes decisions on sensing in order to achieve certain well-defined objectives such as improving spatial coverage of sensing and detection of hotspots. The system is programmable in that our framework allows one to create custom smart systems by writing custom control logic for sensing. Our contributions are two-fold -- a backend software stack to enable centralized control of distributed devices and programmability, and algorithms for intelligent control in the presence of practical power and network constraints. We briefly present three different urban sensing applications built on top of the MUSIC stack.