A Novel AI-Based LED Grow Light

Indoor farming offers the opportunity to grow produce close to the consumer and has recently been gaining attention due to its efficiency, controllability, and sustainability. In indoor farming, food is grown indoors in a controllable environment, with stable environmental conditions. This approach reduces the land footprint required, the demand for energy and water, the nutrient input requirements, and can eliminate the need for pesticides. Food can be locally produced, picked, packed, and quickly delivered to neighbouring communities.
In this research program, next-generation AI-based LED grow lights tailored for future vertical farming will be designed and developed. The proposed solution will offer high efficiency and great flexibility as it can adjust the light intensity and spectrum accordingly. The firmware embedded in the proposed AI-based LED grow lights can identify issues in the growth process and adaptively change the outputs.

Faculty Supervisor:

Majid Pahlevani

Student:

Behzad Poorali Raibi;Ramu Nair;Ujwal Thakur

Partner:

Genoptic LED Inc

Discipline:

Engineering - computer / electrical

Sector:

Professional, scientific and technical services

University:

Queen's University