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AI-enabled supply chain: A win-win for farmers, consumers

Technology can play a big role in terms of efficient long-term storage and processing and in improving the supply chain

By Prakash Kumar

Have you ever thought about how vegetable and fruit stocks get replenished at our neighbourhood shops? How do these perishable and delicate products arrive at the shop, neatly stacked, without damage? More questions to ponder: Why does the farmer get Rs 10 for a kilogram of tomatoes, which we consumers buy at Rs 40 per kilogram from the vegetable shop? How are the margins determined?

The supply chain, involving many actors, is highly inefficient, leading to a lot of wastage, which affects your pocket, and there is a solution to the issue.

As Foods and Agricultural Organization (FAO) estimates, more than 40% of food produced is wasted in India. Its costs could be as high as Rs 92,000 crore, with fruits and vegetable wastage alone contributing Rs 40,000 crore.

Loss and wastage decrease their availability in the market, which in turn increases prices and reduces the capacity of low-income consumers to access the same. This loss represents a wastage of water, land, energy and other natural resources used to produce food.

Tackling these losses and waste will lead to higher availability of food and optimise the use of natural and financial resources.

Technology can play a big role in this, one in terms of efficient long-term storage and processing and the other in improving the supply chain.

How does AI improve supply-chain and reduce the big information gap between producer and retailer of vegetables/fruits and lead to a better price for them?

The simplest supply chain starts with the farmer and ends at the neighbourhood retail shop. It goes like this. Farmer Ò Collection Agent in the village Ò Transport agent Ò Adhatiya in Mandi Ò  Wholesaler Ò Neighbourhood Vegetable Retail shop.

In this system, farmers experience price risk, information asymmetry about demand, distribution inefficiency and receive late payments.

On the other hand, the retailers face problems like higher costs, low quality and unhygienic produce, high price volatility, and the everyday hassle of going to the market very early in the morning.

Thus, the traditional ‘Supply Chain’ is highly inefficient, unorganised, and has a high food wastage rate.

The main reason is the lack of proper information amongst various actors, which leads to price manipulation by intermediaries who hedge their risk by jacking up the price. The ultimate sufferers are farmers and consumers.

So, how does AI help? Based on analysis of past data, projections are made by the system, which is shared with farmers one week in advance via SMS in the local language.

This advice is further updated after five days based on market rates, supply and demand during the previous few days.

Collection centres are set up in rural areas where farmers bring their produce as per SMS received by them.

The produce is sorted based on quality and weight, and then packed in plastic crates. These are then sent to large fulfilment centres where the second round of quality check is done, and based on orders received from various retailers, crates are grouped.

The crates are transported in trucks, routes for which are planned by AI system. The driver delivers the crates, collects the empty crates along with money from retailers.

This reduces loss or wastage, takes away information asymmetry and removes multiple layers of intermediaries leading to consistent demand and better price to producers and fair price to consumers.

Retailers receive fresh produce at competitive prices that are delivered to their shops. This, in turn, helps build reliable, cost-effective, and high-speed logistics and infrastructure.

The power of AI and computer vision has been used to solve another big challenge facing this eco-system, i.e. quality assessment of fresh fruits and vegetables.

The AI-based system has cameras and sensors that are used to visualise food in the same way that consumers do.

These systems are trained on colour, size and other parameters of various types of vegetables and fruits and thus can assess the quality and then sort them.

AI removes human bias from quality inspection, offering objective results instantly and optimising the quality.

The automated packing system can be attached to the sorting system to pack vegetables in lots of 500 grams to a kilogram or more in nylon nets.

This enables printing of source and lot numbers etc., which will lead to complete traceability of every packet. Traceability enables quick identification of the source in case of contamination and disease.

By keeping a record of the entire production and distribution history, farmers can react quickly to issues like bad quality seed or pesticide used etc.

Production history at the farm level can also provide better advisory to farmers and channelise help provided by the government, especially to small farmers. This data will also be useful for better planning of new processing and storage facilities.

To ensure hygienic conditions in quality-cum-sorting centres, cameras can be put to monitor workers and object recognition software used to determine whether workers wear gloves and masks as required by food safety laws.

Is this a pipe dream? Not exactly, as few startups from Bangalore used AI-based supply-chain systems during the first wave of the COVID-19 pandemic, and they have flourished since then.

AI-enabled supply-chain systems are operational in seven major cities – Bangalore, Chennai, Hyderabad, Delhi, Ahmedabad, Pune, Mumbai. I hope it pans out to more cities bringing fruits of technology-led intervention and helps benefit farmers and consumers.

Source: Business Today

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