Experience Paper: Adopting Activity Recognition in On-demand Food Delivery Business
Fuente:
arXiv
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| Autori principali: | , , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2025
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| Soggetti: | |
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| _version_ | 1866915521192001536 |
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| author | Xu, Huatao Zhang, Yan Gao, Wei Shen, Guobin Li, Mo |
| author_facet | Xu, Huatao Zhang, Yan Gao, Wei Shen, Guobin Li, Mo |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2509_24303 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Experience Paper: Adopting Activity Recognition in On-demand Food Delivery Business Xu, Huatao Zhang, Yan Gao, Wei Shen, Guobin Li, Mo Artificial Intelligence Human-Computer Interaction 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. |
| title | Experience Paper: Adopting Activity Recognition in On-demand Food Delivery Business |
| topic | Artificial Intelligence Human-Computer Interaction |
| url | https://arxiv.org/abs/2509.24303 |