Solution

Designed and built a system leveraging robotic data collection to enable machine learning based analytics to forecast harvests, model the spread of pests and disease and optimise crop interventions for plant health.

Tech Stack

The hardware developed was designed to retro-fit to existing commercial greenhouse mobility systems to reduce barriers to entry. It incorporated patented 360 stereo-depth machine vision hardware & edge-AI image stitching for use in a bandwidth-constrained environment.

Leadership

• Led development of new product roadmaps, leveraging market, user & technology research to make strategic decisions with C-suite

• Recruited & supervised a team of 6 engineers & guided them to. Acted as the final review on all engineering change orders

• Drove the adoption of lean & agile methodologies for product development, owning feature backlog, running scrums, conducting reviews & retrospectives, & serving as the voice of the customer

• Continuously ran A/B trials in the field to make design decisions supported by user data

• Identified & led engagement with key technology partners

Impact

• Launched 6 robotics & sensing products to market

• Reduced cost & failure rates by 30% & manufacturing time by 80% compared with legacy products

• Scaled manufacturing 10x

• Author of 3 patents covering the robotic collection, analysis & use of climate data