Experience Paper: Adopting Activity Recognition in On-demand Food Delivery Business
This paper presents the first nationwide deployment of human activity recognition (HAR) technology in the on-demand food delivery industry. We successfully adapted the state-of-the-art LIMU-BERT foundation model to the delivery platform. Spanning three phases over two years, the deployment progresses from a feasibility study in Yangzhou City to nationwide adoption involving 500,000 couriers across 367 cities in China. The adoption enables a series of downstream applications, and large-scale tests demonstrate its significant operational and economic benefits, showcasing the transformative potential of HAR technology in real-world applications. Additionally, we share lessons learned from this deployment and open-source our LIMU-BERT pretrained with millions of hours of sensor data.
Authors
- GG Shen
- Huatao Xu (ORCID: https://orcid.org/0000-0002-8289-0910)
- Mo Li (ORCID: https://orcid.org/0000-0002-6047-9709)
- Yan Zhang (ORCID: https://orcid.org/0000-0002-7904-0982)
- Wei Gao
Institutions
- Hong Kong University of Science and Technology (HK)
- Alibaba Group (China) (CN)
Publication Details
- Published
- 2025-11-03
- DOI
- https://doi.org/10.1145/3680207.3765261
- Primary Topic
- Context-Aware Activity Recognition Systems
- Type
- article
- Field-Weighted Citation Impact
- 0.00