Newton Fund - LIVEQuest: A self-contained wearable Internet-of-Things System for Precision Livestock Agriculture
Lead Participant:
QUEEN MARY UNIVERSITY OF LONDON
Abstract
Worldwide demand for meat and animal products is set to increase by c.40% over the next decade; China's total meat production quadrupled in the last 20 years due to rising demand from a rapidly growing population. However, environmental/public health issues are becoming more prominent in China (as with all emerging
economies), and sustainable intensification of livestock agriculture is a key concern of Chinese policy-makers & stakeholders. This project merges a team of interdisciplinary experts in animal behaviour, Internet-of-Things (IoT),wearable computing & veterinary diagnostics to develop a highly innovative Smart Wearable IoT platform and Decision Support System for precision livestock farming (with an initial focus on poultry). A fully-networked Smart farmers' boot is proposed to assess animal welfare and farm environment at flock eye-level, allowing ubiquitous, non-obstructive, automated data collection. Guangxi province farm data will standardise animal health and welfare indices for China.This will improve farm productivity, animal welfare, smallholder livelihood and consumer nutrition, contributing to economic development and welfare of the Chinese population.
economies), and sustainable intensification of livestock agriculture is a key concern of Chinese policy-makers & stakeholders. This project merges a team of interdisciplinary experts in animal behaviour, Internet-of-Things (IoT),wearable computing & veterinary diagnostics to develop a highly innovative Smart Wearable IoT platform and Decision Support System for precision livestock farming (with an initial focus on poultry). A fully-networked Smart farmers' boot is proposed to assess animal welfare and farm environment at flock eye-level, allowing ubiquitous, non-obstructive, automated data collection. Guangxi province farm data will standardise animal health and welfare indices for China.This will improve farm productivity, animal welfare, smallholder livelihood and consumer nutrition, contributing to economic development and welfare of the Chinese population.
Lead Participant | Project Cost | Grant Offer |
---|---|---|
QUEEN MARY UNIVERSITY OF LONDON | £404,916 | |
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Participant |
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BMCE NETWORKS LIMITED | £128,483 | £ 89,938 |
QUEEN MARY UNIVERSITY OF LONDON | ||
GRID SMARTER CITIES LTD | ||
AGSENZE LTD | £271,635 | £ 190,145 |
INNOVATE UK | ||
CROP INNOVATIONS CIO |
People |
ORCID iD |
Yue Gao (Project Manager) |