eBaaS: AIoT-Enabled eBike Battery-Swap as a Service for Last-Mile Delivery

  • Donghui Ding
  • , Zhao Li*
  • , Jiarun Zhang
  • , Xuanwu Liu
  • , Ji Zhang
  • , Yuchen Li
  • , Peng Cai*
  • , Jian Xun Liu
  • , Guodong Long
  • *Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

In China, the number of riders in the on-demand delivery industry has surpassed ten million. Ensuring that these riders earn a decent income can enhance their financial security, reduce poverty, and promote social equity and stability. Due to ease of use, lower-cost maintenance and environmental friendliness, electric bicycles (e-bikes) are the primary mode of transportation for delivery riders. However, these riders frequently encounter depleted batteries due to limited capacity and prolonged charging times, necessitating inconvenient swaps or recharges during deliveries. To address this issue, we propose the e-bike Battery Swap-as-a-Service (eBaaS), an innovative battery-swapping system that leverages an intelligent AIoT network for seamless battery swapping at distributed locations across urban areas. eBaaS integrates edge-cloud collaboration, battery resource allocation, battery anomaly detection, and battery range prediction to minimize downtime and reduce unnecessary mileage. While eBaaS’s potential benefits are evident, there has been a lack of robust methods to quantify its impact. Thus, we further developed the eBaaS Impact Evaluation Method (EIEM), the first comprehensive model to address this gap. EIEM analyzes data from approximately 260,000 delivery riders and 5 million riding trajectories. Findings indicate that eBaaS reduces average invalid mileage by 6 km and increases the order volume by an average of over 20% daily per e-bike rider. Meanwhile, the annual electricity savings result in a reduction of 2.74 million kilograms of carbon emissions for 260,000 riders. The eBaaS system is therefore significantly beneficial for environmental conservation and sustainable urban development.

Original languageEnglish
Title of host publicationWWW 2025 - Proceedings of the ACM Web Conference
PublisherAssociation for Computing Machinery, Inc
Pages5045-5053
Number of pages9
ISBN (Electronic)9798400712746
DOIs
StatePublished - 28 Apr 2025
Event34th ACM Web Conference, WWW 2025 - Sydney, Australia
Duration: 28 Apr 20252 May 2025

Publication series

NameWWW 2025 - Proceedings of the ACM Web Conference

Conference

Conference34th ACM Web Conference, WWW 2025
Country/TerritoryAustralia
CitySydney
Period28/04/252/05/25

Keywords

  • Battery Anomaly Detection
  • Battery Range Prediction
  • E-bike Battery-swapping System
  • Edge-cloud Collaboration

Fingerprint

Dive into the research topics of 'eBaaS: AIoT-Enabled eBike Battery-Swap as a Service for Last-Mile Delivery'. Together they form a unique fingerprint.

Cite this