{"ID":2863309,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2509.24303","arxiv_id":"2509.24303","title":"Experience Paper: Adopting Activity Recognition in On-demand Food Delivery Business","abstract":"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.","short_abstract":"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...","url_abs":"https://arxiv.org/abs/2509.24303","url_pdf":"https://arxiv.org/pdf/2509.24303v1","authors":"[\"Huatao Xu\",\"Yan Zhang\",\"Wei Gao\",\"Guobin Shen\",\"Mo Li\"]","published":"2025-09-29T05:35:49Z","proceeding":"cs.AI","tasks":"[\"cs.AI\",\"cs.HC\"]","methods":"[]","has_code":false}