Experience Paper: Adopting Activity Recognition in On-demand Food Delivery Business
Xu, Huatao, Zhang, Yan, Gao, Wei, Shen, Guobin, Li, Mo
–arXiv.org Artificial Intelligence
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.
arXiv.org Artificial Intelligence
Sep-30-2025
- Country:
- Asia > China
- Guangdong Province
- Hong Kong (0.06)
- Shaanxi Province > Xi'an (0.04)
- Shanghai > Shanghai (0.04)
- Europe > United Kingdom
- England > Cambridgeshire > Cambridge (0.04)
- North America > United States
- New York > New York County > New York City (0.04)
- South America > Argentina
- Pampas > Buenos Aires F.D. > Buenos Aires (0.04)
- Asia > China
- Genre:
- Research Report > New Finding (1.00)
- Industry:
- Technology: