SmartParcels: Constructing Smart Communities Through Human-in-the-Loop Urban IoT Planning

  • Tung Chun Chang
  • , Chih Chun Wu
  • , Georgios Bouloukakis
  • , Cheng Hsin Hsu
  • , Nalini Venkatasubramanian

Research output: Contribution to journalArticlepeer-review

Abstract

The growth of smart communities has expanded the use of IoT as a critical element in the urban planning toolkit by city officials whose goal is to improve the quality of life for citizens. Smart applications such as air-pollution monitoring, intelligent transportation, and smart buildings pose diverse information needs from the underlying sensing, communication, and computation infrastructure. In this article, we propose SmartParcels, a framework that exploits the service needs of communities to generate a comprehensive and cost-effective plan for instrumenting designated regions (often called parcels). SmartParcels embeds a cross-layer approach incorporating information/data, infrastructure, and geospatial layout as interdependent layers. We explore a suite of algorithms (optimal, partial optimal, heuristic) that can be composed in a plug-and-play manner to achieve performance-cost tradeoffs. SmartParcels can be utilized for clean-slate planning (from scratch) or retrofitting communities with existing smart infrastructure. SmartParcels allows planners to explore the possible impact of unexpected events to improve infrastructure resilience with what-if analyzers. Two real-world settings at Hsinchu, Taiwan, and Irvine, California, are leveraged in the evaluation, which reveals that SmartParcels enables a 2×-7× improvement in cost/performance metrics compared to baseline algorithms and achieves a 57% higher communication throughput while dealing with unexpected events.

Original languageEnglish
Article number10
JournalACM Transactions on Internet of Things
Volume6
Issue number2
DOIs
Publication statusPublished - 14 Apr 2025

Keywords

  • Additional Key Words and PhrasesIoT planning
  • human-in-the-loop
  • placement problem
  • urban planning
  • what-if analysis

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