Can Data Science help control food wastage in Mumbai

AI and Data Science Course are helping to decrease food waste.Today, food waste is a pressing worldwide concern. According to FAO, the United Nations Food and Agriculture Organization, one-third of all food produced for human consumption is wasted globally each year, equal to 1.3 billion tons of food. This is bad for everyone, not only the economy and society, but also the environment. Producing and disposing of uneaten food wastes valuable resources and emits needless pollutants. Data Science and Artificial Intelligence may assist to improve this negative scenario, assuring a significant reduction in waste across the supply chain, from producer to individual customer.

Food Wastage in Numbers Worldwide:

Every year, more than enough food is produced throughout the world to feed the whole global population. Nonetheless, 811 million people are hungry every day. World hunger affects 9.9% of the world population.

It is alarming that over one-third of all food produced, or around 1.3 billion tons, is wasted, with 95% of rejected food ending up in landfills or burning sites.

If food waste were a country, it would be the third largest national emitter of greenhouse gases after the United States and China. Food losses and waste account for about 6% of total greenhouse gas emissions.

In India:

India wastes 20-25% of food from farmer field to consumer plate, including prepared meals, which may be reduced to 10-15% with the use of technology. In restaurants, reducing food waste must begin with the supply. AI may aid by rationalizing orders based on the kitchen’s real demands. By suing AI’s predictive algorithm we can save tons of food on a daily basis which means hundreds of thousands of people wouldn’t go to bed with empty stomachs.

What Areas to Improve?

Food production:

Crop optimization is one way that data science may help reduce waste in food production. Data collected by drones, remote sensors, satellites, and intelligent agricultural equipment may give producers with useful information regarding soil production capacity, crop health, and weather patterns. If expanded upon, this knowledge may assist farmers in making more informed choices regarding crop rotation, sowing periods, and the best time for harvesting and composting.

Distribution:

Real-time analysis, which monitors important factors, may identify deteriorations that eventually lead to food waste. Again, this efficiency can only be accomplished by combining useful sensor data with sophisticated analysis algorithms capable of reprocessing and raising warnings before certain situations exist.

Stores:

Shopkeepers may, for example, prepare a correct rotation of goods on the shelves and even plan special promotions before the expiry dates are exceeded. AI algorithms may also assist anticipate sales of certain items in comparison to others, which is a significant contribution when ordering goods.

Consumers:

The emergence of smart systems capable of automating various functions and sending notifications to users makes a significant contribution to reducing food waste at home. These systems are known as’smart fridges’. These Internet-connected and app-managed gadgets enable users to input the purchase date of each refrigerated product, and they send an alarm when the expiry date approaches.

Some International Case Studies:

To solve the issue of food waste, grocery store chains, food tech businesses, and meal-kit companies are increasingly using sustainable and scalable open-source technology.

In 2020, the LMK Group, a Nordic food technology firm, distributed around 1.74 million meal kits straight to customers’ doorsteps. It employs a proprietary Machine Learning Model developed on Azure to forecast client orders. This forecast has helped LMK achieve a food waste rate of 1% or less in the manufacturing sector. It does this by providing food farmers and suppliers with exact forecasts up to 10 weeks in advance, allowing them to avoid growing products that they may not need.

Food storage generates a substantial amount of waste. Danfoss, a Danish company, has devised a monitoring service that employs sensors to verify that freezers and refrigerators in grocery shops maintain a certain temperature and warns personnel if there is a violation. This keeps food from spoiling and increases the shelf life of food goods.

Migros, a Turkish store, utilizes AI monitors to verify stock levels at racks. It creates warnings about their condition, allowing the retailer to prioritize and promote certain goods. Bizerva, a German retail technology company, integrates revolutionary weighing equipment with retail shelving systems that can monitor and inspect inventory. Using IoT and dynamic pricing, full-shelf products’ prices are reduced in real time, making them more appealing to buyers and decreasing waste.

Possible Solutions:

Big Data Analytics may help identify the stages in the food distribution and consumption chain where loss may occur. The following are some of the improvements that may reduce the quantity of food waste overall:

1. Implementing Technology to improve Inventory Management:

Using cutting-edge technology may assist minimize excess inventory and the quantity of perishables that are eventually destroyed as a result of inefficient handling systems. A variety of minimum viable products (MVPs) are now being developed and evaluated. If successful, they will provide access to a plethora of chances in inventory system development.

2. Coordination in the Supply Chain:

Food waste begins with the land where it is cultivated. Approximately 7% of all product is wasted on the farm. This inclination to develop excessively is sometimes seen as a protective measure against severe weather and infections. However, by working directly with middlemen and farmers, merchants may minimize a significant amount of waste.

3. Change Conventional Storage Practices:

Over time, the market has shifted heavily toward visually beautiful produce. As a result, fruits and vegetables with minor flaws are discarded, resulting in significant food waste.

Another habit that adds significantly to food waste is product labeling. For example, people often mix best-buy dates with expiry dates and reject food. Many nations suffer from a lack of conventional labeling practices, resulting in a significant amount of food waste.

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