About
Innowise incorporated computer vision technology into self-driving agricultural robots, enabling them to automatically feed plants and remove weeds with lasers. Our client is a company producing autonomous agricultural robots to automate and accelerate farm work within the European region.
Challenge, approach, and impact
Challenge: Overcoming limitations of manual plant care with AI technology in agriculture
ML farms and robots address agriculture's labor shortages, high costs, and inefficiencies in manual plant care. These technologies boost resource efficiency amid growing challenges. Our client develops autonomous robots/devices to automate cultivation and plant nurturing. Capable of navigating beds/fields, they lacked plant-weed differentiation for precise, selective fertilization/watering. Innowise stepped in with ML vision solutions.
Challenge:
Our experts integrated specialized ML software into robots to accurately distinguish thinned-out plants from weeds. The system enabled precise laser-based weed removal, identified plant types, and dispensed optimal fertilizer based on class and condition metrics for resource-efficient care. Scope included: data collection; manual markup; augmentation; model training; seamless model integration into robotics; real-time inference/processing for field deployment.
How we built
Testimonials
Anonymous
“Our AI ag robot solution exceeded expectations delivering 64% fertilizer savings and 100% pesticide/human resource reduction MVP. Their custom neural nets enabled precise, offline weed lasering and plant care, transforming our automation vision into a scalable reality.“
Team structure
Client team
Peter
Product Owner
The client stakeholders were working closely with the team at Innowise Sp. z o.o
Agency team
Machine Learning Engineer
Production
Backend Engineer
Production
Project Manager
Production
