Computer vision is already being used to bring analytics to retailers, identify early signs of Alzheimer's, and even to identify weapons, but ImpactVision is leveraging the power of machine learning to automatically assess the quality of food in factories and warehouses. Based in San Francisco, the startup has already garnered $1.6 million in funding and recently received another $1.3 million. This new round of funding would be used to "accelerate product development" and grow other sectors of the company.
Ultimately, the technology developed by ImpactVision aims to cut food waste globally by utilizing the technological landscape. In addition to machine learning, the technology driving ImpactVision also utilizes spectroscopy. This process allows the AI to better assess the quality of the food beyond just a surface level view.
Food-Analyzing Machine Learning
ImpactVision is Using AI to Eliminate Food Waste
Trend Themes
1. Machine Learning in Food Analysis - Opportunity to revolutionize the food industry by using machine learning to automatically assess food quality and reduce waste.
2. Computer Vision in Agriculture - Disruptive innovation opportunity in using computer vision to analyze the quality of food in factories and warehouses.
3. Utilizing Spectroscopy for Food Quality Assessment - Opportunity to enhance food assessment beyond surface level analysis by incorporating spectroscopy technology.
Industry Implications
1. Food Industry - Machine learning and computer vision can be applied in factories and warehouses to improve food quality and reduce waste.
2. Agriculture - Computer vision and machine learning can be used to automate the assessment of food quality in warehouses and increase efficiency.
3. Technology - Spectroscopy and machine learning technologies can be integrated to enhance food quality assessment in various industries.