A few years back, a scientist developed food labels that told you when fruits and vegetables were ripe (which I still haven't seen at the grocery stores). Well, now a group of scientists at Manchester University have developed another set of food labels, this time telling us when the food is about to go bad.
It is hoped that this technology could be used to contact us via messages to our cellphones. Business meetings may soon sound like this: "Excuse me, I have to take this call. Hello? Oh, my sour cream is going bad? OK. Thanks."
-Photo from jeffk (Flickr)
Food That Texts You When It Spoils
Mold Alerts
Trend Themes
1. Smart Food Labels - Smart labels that track food freshness and send notifications via cellphones are a disruptive innovation opportunity for food retail and distribution industries.
2. Real-time Food Monitoring - Real-time food monitoring via IoT-enabled smart labels is a disruptive innovation opportunity for food safety and quality control industries.
3. Personalized Food Notification - Personalized notification systems for food freshness based on individual consumption patterns is a disruptive innovation opportunity for the food industry, particularly in reducing food waste at consumer level.
Industry Implications
1. Food Retail - Smart food labels that track food freshness and send notifications present a disruptive innovation opportunity for food retail industry, especially as consumers become more conscious of food waste and demand better quality control measures.
2. Food Safety and Quality Control - Real-time food monitoring via IoT-enabled smart labels is a disruptive innovation opportunity for food safety and quality control industries, who can leverage the data to prevent potential outbreaks, recall contaminated products and improve production processes.
3. Smart Packaging - Personalized notification systems for food freshness based on individual consumption patterns is a disruptive innovation opportunity for smart packaging industry, which can incorporate tracking and communication features for food products with the help of machine learning and AI technologies.