Machine vision is revolutionizing the food and agriculture industries by enhancing efficiency, ensuring quality, and reducing waste. In agriculture, machine vision systems can be employed to monitor crop health, detect diseases, and optimize harvesting by analyzing images of plants in real-time. This technology enables precision farming, where resources like water and fertilizers are applied more effectively, leading to increased yields and sustainability. Moreover, in R&D, machine vision provides researchers with detailed, high-resolution data that can be used to study plant growth patterns, test new agricultural techniques, and develop innovative food processing methods. In the food industry, machine vision is used for quality control, ensuring that products meet specific standards by detecting defects, sorting items by size, and verifying packaging accuracy. These advancements not only improve product quality and safety but also streamline operations, reduce labor costs, and minimize waste, contributing to a more sustainable and profitable agricultural sector.
The Need
The client is an international grower of cuttings and flowers. As part of its continuous R&D process, the client needs to systematically measure the flowers in their pots and correlate that to the given biological and physical treatment along growing time. This kind of complex phenotyping not only sets the client apart by achieving a longer “shelf life” for the flowers, it also has the ability to grow hybrid flowers, creating outstanding unique and beautiful new flowers.
The Challenge
The Solution
Design and development of a 3D scanning unit. The system can scan small and large pots in less then 30 seconds enabling the handling of a large amount of monitored pots. The project development included software, mechanical, optical and electronic design, and complete manufacturing of the unit. After each scan, a complete 3D model of the plant is automatically calculated together with a 3D analysis that includes segmentation of flowering, foliage, pot, color detection and fitting to predefined spatial shapes. All this data is also analyzed offline later to create a recommendation and prediction of future results. The scanner has a user-friendly interface and the ability to save and manage previous scans to support various experimental setups.
The Need
The client is an entrepreneur in the food industry equipment sector. As part of his in-depth understanding of his clients’ needs, he noticed the occurrence of unnecessary workplace accidents during fish or meat cutting using dedicated bandsaws. The client clearly defined the failure points and situations where accidents occur, in order to design a safety system capable of stopping the bandsaw before it injures the operator. The system was also required to provide protection without limiting the operator’s work through false stops or frequent blade replacements.
The Challenge
The Solution
Design and development of an optical system installed and tested on a typical bandsaw. A fast algorithm implemented on a rugged embedded platform detects hand entry into one of several controlled coverage areas. A rapid, durable communication system was established to interface with the mechanical controller of the system, enabling immediate saw stoppage.
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