This inventor holds 1 USPTO granted patent. Top assignee: Croptimistic Technology Inc.. Active years: 2026.
Data source: USPTO (United States Patent and Trademark Office) public patent records. Weekly synchronization. How IDiyas builds this profile
Company Filing History:
Years Active: 2026
Title: Innovations by Abdul Bais in Agricultural Technology
Introduction
Abdul Bais is an innovative inventor based in Regina, Canada. He has made significant contributions to the field of agricultural technology through his inventive work. His focus on utilizing machine learning processes to enhance agricultural practices has garnered attention in the industry.
Latest Patents
Abdul Bais holds a patent for a method and system for automatically capturing and extracting data from images of agricultural field crops and weeds. This invention allows for the automatic collection of data from images of crops, weeds, and soil within management zones that represent soil, water, and topography (SWAT) features of a field. The camera system is designed to be mounted on any vehicle that traverses agricultural fields. The images captured are automatically uploaded to a processing server for analysis by farmers and agricultural service providers. The use of machine learning processes enables the documentation of critical weed and crop data by SWAT management zone and entire fields.
Career Highlights
Abdul Bais has made a notable impact in the agricultural sector through his innovative solutions. His work at Croptimistic Technology Inc. has positioned him as a key player in advancing agricultural technology. His patent reflects his commitment to improving efficiency and data management in farming practices.
Collaborations
Abdul collaborates with talented individuals such as Stuart Hassall and Corwyn Willness. Their combined expertise contributes to the development of cutting-edge agricultural technologies.
Conclusion
Abdul Bais is a pioneering inventor whose work in agricultural technology is transforming the industry. His innovative patent demonstrates the potential of machine learning in enhancing agricultural practices.
Data source: USPTO (United States Patent and Trademark Office) public patent records. Weekly synchronization. How IDiyas builds this profile