mlsanityData to 14 Oct 2026

Experience Paper: Adopting Activity Recognition in On-demand Food Delivery Business

arXiv 2509.24303 ↗First posted 29 Sep 2025cs.AI cs.HCcited by 1

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Abstract (arXiv)

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.

Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 12 of its 57 references that are in the map. First posted on arXiv 29 Sep 2025.

Builds on

12 of 57 references.

References · 12

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  8. 2022Assessing the State of Self-Supervised Human Activity Recognition using Wearablescited by 65
  9. 2022What Makes Good Contrastive Learning on Small-Scale Wearable-based Tasks?cited by 40
  10. 2021SelfHAR: Improving Human Activity Recognition through Self-training with Unlabeled Datacited by 31
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  12. 2025Scaling laws in wearable human activity recognitioncited by 4

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2026: 1.

1 paper.

  1. 2026BenchHAR: Benchmarking Self-Supervised Learning for Generalizable Sensor-based Activity Recognitioncited by 2