DeMo: Experiences of Deploying a Large-Scale Indoor Delivery Monitoring System

Xiubin Fan, Zhongming Lin, Yuming Hu, Zhiqing Hong, Tianrui Jiang, Feng Qian, Zhimeng Yin*, S.-H. Gary Chan, Dapeng Oliver Wu

*Corresponding author for this work

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

Abstract

The delivery of goods to numerous indoor stores poses significant safety risks, with heavy, high-stacked packages on delivery trolleys posing a potential hazard to passersby. This paper reports our experiences of developing and operating DeMo, a practical system for real-time monitoring of indoor delivery. DeMo employs sensors attached to trolleys, utilizing Inertial Measurement Unit (IMU) and Bluetooth Low Energy (BLE) readings to detect delivery violations, such as speeding and the use of non-designated delivery paths, and ensure accurate matching of each delivery to its intended destination store. Unlike typical indoor localization applications, DeMo addresses unique challenges, including sensor placement and the complex electromagnetic characteristics encountered in underground settings. Specifically, DeMo adapts the classical logarithmic radio signal model to facilitate fingerprint-free localization, significantly reducing deployment and maintenance costs. DeMo has been operating since May 2020, covering more than 200 shops with 74,537 deliveries (6193.2 km) across 12 subway stations in Hong Kong. DeMo's 4-year operation witnessed a significant violation rate drop, from 19% (May 2020) to 0.9% (Mar 2024).

© 2025 IEEE
Original languageEnglish
Number of pages18
JournalIEEE Transactions on Mobile Computing
DOIs
Publication statusOnline published - 29 Jul 2025

Funding

This study was supported by NSF China 62102332, CityU 21216822, CityU APRC 9610491, and CityU 11206023.

Research Keywords

  • Sensor network
  • mobile computing
  • Bluetooth Low Energy

RGC Funding Information

  • RGC-funded

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