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World's First High-Efficiency AI · Edge AI
SingTown Technology is the official founding team of OpenMV. In 2016, we launched the world's first embedded machine vision product, OpenMV Cam, which is the first product to run image algorithms on embedded MCUs, also the world's first High-Efficiency Edge AI smart camera.
The OpenMV Cam is a computer vision board for all industries that breaks the tension between performance, power and price. The OpenMV Cam enables customers to run AI deep learning models and advanced computer vision functions (object detection, object classification, tracking, etc.) in real-time, for years off of battery power, for low cost per unit.
The OpenMV Cam is a general purpose MicroPython powered microcontroller platform with camera input and computer vision processing as well as high performance AI machine learning features already onboard. Sense, plan, and act using MicroPython to control general-purpose I/O pins that can do I2C/SPI/PWM/etc. along with being able to read/write files and talk to the internet through wifi/ethernet.
SingTown Technology is a leader in the embedded machine vision industry, serving over 3,000 universities and 20,000 enterprises around 100+ countries worldwide. Our vision is to practice social responsibility and drive social progress through technology.
SingTown Technology Assists in Creating an Intelligent Fruit and Vegetable Sorting System That "Understands Produce" and "Is Easy to Deploy
The fruit and vegetable processing equipment manufacturer adopts SingTown Technology's OpenMV intelligent camera AI image recognition solution, utilising AI visual algorithms to achieve fruit volume detection and surface quality identification, automatically completing grading and sorting, significantly enhancing the automation and consistency of fruit and vegetable processing.
Resolving the "Difficult Deployment" of Intelligent Harvesting, SingTown Technology Bridges the "Last Mile" of Agricultural Intelligence
Agricultural equipment enterprises utilise SingTown Technology's OpenMV intelligent camera edge AI image recognition algorithm to achieve fruit and vegetable maturity identification and precise picking control, enhancing picking efficiency and intelligence levels, thereby contributing to the development of smart agriculture.
Accurate identification of broadleaf weeds within 0.5 seconds, SingTown technology drives agricultural machinery upgrades.
Agricultural intelligent devices utilise the SingTown OpenMV smart camera to achieve automatic identification and control of broadleaf weeds in fields for spraying or weeding operations, enhancing weeding efficiency and reducing pesticide usage.
Fish falls ill, SingTown Technology OpenMV knows first.
Aquaculture manual detection of fish diseases is inefficient and susceptible to lighting and water quality influences. By utilising SingTown OpenMV smart cameras and AI vision, real-time identification of fish diseases such as white spots, tail and fin rot is achieved, enhancing the efficiency and accuracy of health monitoring.
SingTown Technology's visual AI empowers agricultural equipment to achieve automated plastic film detection.
Manual inspection of agricultural machinery for plastic film is inefficient and prone to missed detection. By utilising the SingTown OpenMV smart camera and AI vision technology, film width detection and damage identification are achieved, enabling real-time monitoring of laying quality and enhancing operational efficiency and intelligent capabilities.
Not only the fish know when the fish tank is dirty; SingTown's water quality monitoring system "sees the dirt and cleans automatically.
Manual water quality monitoring through visual observation is time-consuming and subjective, making continuous detection difficult. By employing the SingTown OpenMV smart camera and AI vision technology, automatic identification and analysis of sediment, silt, and algae deposits at the bottom of transparent containers are achieved, thereby enhancing monitoring efficiency and intelligence.
The seedling cultivation system integrates AI vision, and SingTown Technology enables cameras to "help you farm.
Agricultural equipment manufacturers adopt SingTown's OpenMV intelligent camera image recognition technology, utilising AI visual algorithms to achieve automatic detection and statistics of "seedling presence/empty holes" in seedling trays, significantly enhancing the automation and standardisation levels of the seedling cultivation process.
SingTown Technology gives lawn mowers 'eyes': they can distinguish crops from weeds and navigate around them on their own.
SingTown Technology's intelligent camera system, based on OpenMV, can be installed on field weeding machines to achieve intelligent identification and tracking of operational and non-operational areas. Through AI and machine vision algorithms, the system distinguishes crops from weeds, precisely controls weeding paths, avoids accidental damage to crops, and provides an efficient, intelligent visual navigation solution for modern agricultural automation.
Mold spots and cracks on rice grains cannot escape the sharp detection of SingTown Technology's AI vision.
SingTown Technology's intelligent camera system based on OpenMV enables automatic identification of surface cracks and mould spots on rice grains. Utilising machine vision and image recognition technology, the system captures minute cracks, mould growth, or colour abnormalities, providing high-precision, intelligent detection solutions for grain processing, quality inspection, and food safety.
24/7 Online AI "Nanny" for Plants and Animals – SingTown Technology Real-Time Monitoring Solution
SingTown Technology's OpenMV-based intelligent camera system enables automatic identification and monitoring of the growth status of plants, animals, and insects. Utilising machine vision and image recognition technology, the system distinguishes different growth stages based on characteristics such as body size, morphology, or colour. It provides real-time data support and intelligent analysis tools for agriculture, scientific research, and ecological monitoring.
