{"id":{"repo_id":"mit","oai_identifier":"oai:dspace.mit.edu:1721.1/144823"},"canonical_url":"https://search.dev.ndltd.org/etd/mit/oai:dspace.mit.edu:1721.1/144823","repository":{"repo_id":"mit","name":"MIT","base_url":"https://dspace.mit.edu/oai/request"},"display":{"title":"Development of Wireless Sensor Network to Detect Lameness in Dairy Cows","abstract":"Bovine mastitis, lameness, and calving are three major problems in the dairy farming industry. They lead to economic losses and decreased animal welfare. With the industrialization of dairy farms, these problems are magnified due to the lack of skilled labor. This work introduces a design for a wireless sensor network to automate the health monitoring of every cow on a farm. Through the constant monitoring of health statistics, we can make a prediction about the early onset of mastitis, lameness, and calving and therefore reducing the burdens on the farmers. The network architecture is designed to accommodate a large number of cows (1000s) and the size of dairy farms (area >1500000 m²) by combining a short-range and a long-range communication protocol (Bluetooth Low Energy (BLE) and LoRa). This work also explores the use of IMUs for lameness detection in walking gaits. Taking advantage of the holonomic constraints of animal limbs, Principal Component Analysis is able to compress the highly correlated data of locomotion into a smaller dimension in which abnormal gaits can be differentiated.","abstract_html":"Bovine mastitis, lameness, and calving are three major problems in the dairy farming industry. They lead to economic losses and decreased animal welfare. With the industrialization of dairy farms, these problems are magnified due to the lack of skilled labor. This work introduces a design for a wireless sensor network to automate the health monitoring of every cow on a farm. Through the constant monitoring of health statistics, we can make a prediction about the early onset of mastitis, lameness, and calving and therefore reducing the burdens on the farmers. The network architecture is designed to accommodate a large number of cows (1000s) and the size of dairy farms (area >1500000 m²) by combining a short-range and a long-range communication protocol (Bluetooth Low Energy (BLE) and LoRa). This work also explores the use of IMUs for lameness detection in walking gaits. Taking advantage of the holonomic constraints of animal limbs, Principal Component Analysis is able to compress the highly correlated data of locomotion into a smaller dimension in which abnormal gaits can be differentiated.","abstract_has_math":false,"creators":["Nguyen, Thanh Nha"],"institution":"Massachusetts Institute of Technology","degree_name":"Master","degree_level":null,"degree_discipline":null,"degree_department":"Massachusetts Institute of Technology. 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They lead to economic losses and decreased animal welfare. With the industrialization of dairy farms, these problems are magnified due to the lack of skilled labor. This work introduces a design for a wireless sensor network to automate the health monitoring of every cow on a farm. Through the constant monitoring of health statistics, we can make a prediction about the early onset of mastitis, lameness, and calving and therefore reducing the burdens on the farmers. The network architecture is designed to accommodate a large number of cows (1000s) and the size of dairy farms (area >1500000 m²) by combining a short-range and a long-range communication protocol (Bluetooth Low Energy (BLE) and LoRa). This work also explores the use of IMUs for lameness detection in walking gaits. Taking advantage of the holonomic constraints of animal limbs, Principal Component Analysis is able to compress the highly correlated data of locomotion into a smaller dimension in which abnormal gaits can be differentiated."]},{"key":"dc:description.degree","label":"Dc Description Degree","values":["S.M."]},{"key":"dc:title","label":"Title","values":["Development of Wireless Sensor Network to Detect Lameness in Dairy Cows"]}]}],"canonical_facts":{"dc:contributor.advisor":["Hunter, Ian"],"dc:contributor.department":["Massachusetts Institute of Technology. Department of Mechanical Engineering"],"dc:creator":["Nguyen, Thanh Nha"],"dc:date.accessioned":["2022-08-29T16:14:09Z"],"dc:date.available":["2022-08-29T16:14:09Z"],"dc:date.issued":["2022-05"],"dc:description.abstract":["Bovine mastitis, lameness, and calving are three major problems in the dairy farming industry. They lead to economic losses and decreased animal welfare. With the industrialization of dairy farms, these problems are magnified due to the lack of skilled labor. This work introduces a design for a wireless sensor network to automate the health monitoring of every cow on a farm. Through the constant monitoring of health statistics, we can make a prediction about the early onset of mastitis, lameness, and calving and therefore reducing the burdens on the farmers. The network architecture is designed to accommodate a large number of cows (1000s) and the size of dairy farms (area >1500000 m²) by combining a short-range and a long-range communication protocol (Bluetooth Low Energy (BLE) and LoRa). This work also explores the use of IMUs for lameness detection in walking gaits. Taking advantage of the holonomic constraints of animal limbs, Principal Component Analysis is able to compress the highly correlated data of locomotion into a smaller dimension in which abnormal gaits can be differentiated."],"dc:description.degree":["S.M."],"dc:identifier.uri":["https://hdl.handle.net/1721.1/144823"],"dc:publisher":["Massachusetts Institute of Technology"],"dc:rights":["In Copyright - Educational Use Permitted","Copyright MIT"],"dc:rights.uri":["http://rightsstatements.org/page/InC-EDU/1.0/"],"dc:title":["Development of Wireless Sensor Network to Detect Lameness in Dairy Cows"],"dc:type":["Thesis"],"thesis:degree_name":["Master","Master of Science in Mechanical Engineering"]},"updated_at":"2026-07-22T22:21:00Z"}