Assessment of horticultural produce often entails manual inspection, which is subjective, time-consuming and prone to human error. This process can result in a demand–supply mismatch when assessing produce quality and lead to wastage. To address this challenge, Intello Labs has developed an AI and computer vision-based solution for quality assessment referred to as Fruitsort. The solution uses advanced cameras and machine learning to rapidly analyse fresh produce, identifying defects, size and ripeness with objective precision. The solution can be implemented on sorting lines or handheld devices, providing an objective, data-driven assessment of quality in real time that is claimed to be 40x faster than manual sorting. By using computer vision, the solution enables buyers to obtain the required quality of produce, reducing rejection, while farmers receive fair prices pegged to quality.CASE STUDY 2 Computer vision to reduce food waste – Intello Labs Edge IoT refers to an architecture in which data generated through the internet of things (IoT) is processed directly on or near the device (referred to as the edge of the network). This offsets the requirement to send raw data to a centralized cloud for processing, allowing low-latency, real- time insights, and enables quicker autonomous decision-making. Edge IoT can be transformational in agriculture, as many rural regions have low connectivity and thus are not suitable for cloud- based solutions. Use cases of edge IoT, driven by convergences with machine learning, computer vision and GenAI, include irrigation automation, detecting early signs of plant disease or optimizing fertilizer application.3.3 Edge internet of things (edge IoT) Edge IoT has the potential to unlock transformative opportunities for smallholder farmers in low- and middle-income countries. By processing data closer to the source, farmers can access real- time insights on soil health, weather and irrigation without relying on costly connectivity or cloud infrastructure. This enables timely decisions, reduces input waste and builds climate resilience. Daniele Tricarico, Head of Emerging Tech and Central Insights, GSMA Shaping the Deep-Tech Revolution in Agriculture 14

Shaping the Deep Tech Revolution in Agriculture 2025