Grant: Alliance Grants
University of Alberta
$150,000.00
Foundation model-enabled mobile image analytics platform for precision agriculture
EF 2024-25
Résumé
Our 5-year collaboration is dedicated to the effective and efficient analysis of mobile images, particularly those captured by drones and smartphones, in the domain of precision agriculture. Our AI based analytic platform is to take advantage of the recent technical breakthroughs in multimodality foundation models, including specifically the large vision models and the large language models. For the first two years, our primary aim is to devise an AI system that offers real-time guidance to farmers on the best timing to apply fungicide to their canola crops. Addressing the challenge of sclerotinia stem rot, Canada's most economically damaging canola disease, is at the heart of this initiative. The rest of the 5-year partnership will continue to improve our developed system with higher accuracy, faster response, and in particular more user-friendly, as well as to extend the scope of our mobile platform to work with a broader range of precision agriculture applications.
Programme
Alliance Grants
Bénéficiaire
Emplacement
Alberta, Canada
Type de bénéficiaire
Academia
Type
Grant
Source
NSERC's Awards Data
Tel que publié
Application id
592399-2023
Name nom
Cheng, Li L
Department département
Electrical and Computer Engineering
Organization id
9
Institution établissement
University of Alberta
Province en
Alberta
Province fr
Alberta
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2024
Competition year année de concours
2023
Award amount
150000
Program id
ALLRP
Program name en
Alliance Grants
Program name fr
Subventions Alliance
Group en
RESEARCH PARTNERSHIPS
Group fr
PARTENARIATS DE RECHERCHE
Committee code
96
Committee name en
RPP Internal Decision Cttee
Committee name fr
Cté de décision interne - PPR
Area of application code
1209
Area of application group en
Advancement of knowledge
Area of application group fr
Avancement des connaissances
Area of application en
Agriculture
Area of application fr
Agriculture
Research subject code
2603
Research subject group en
Robotics
Research subject group fr
Robotique
Research subject en
Computer vision
Research subject fr
Vision artificielle
Field of research list names en
Not available
Field of research list names fr
Non disponible
Socioeconomic objective list names en
Not available
Socioeconomic objective list names fr
Non disponible
Application title
Foundation model-enabled mobile image analytics platform for precision agriculture
Keywords
canola disease; drone and mobile phone images; foundation models; image analysis; large language models; mobile image processing; multimodal data analytics; natural language processing; precision agriculture; sclerotinia stem rot
Application summary
Our 5-year collaboration is dedicated to the effective and efficient analysis of mobile images, particularly those captured by drones and smartphones, in the domain of precision agriculture. Our AI based analytic platform is to take advantage of the recent technical breakthroughs in multimodality foundation models, including specifically the large vision models and the large language models. For the first two years, our primary aim is to devise an AI system that offers real-time guidance to farmers on the best timing to apply fungicide to their canola crops. Addressing the challenge of sclerotinia stem rot, Canada's most economically damaging canola disease, is at the heart of this initiative. The rest of the 5-year partnership will continue to improve our developed system with higher accuracy, faster response, and in particular more user-friendly, as well as to extend the scope of our mobile platform to work with a broader range of precision agriculture applications.
