Crop Price Forecasts using Algorithm Based Decisions

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Data-Driven Price Forecasts!

agriculture innovation

The challenge

Agriculture is a challenging business, yet it is one of the most important ones globally. When the weather strikes, crops are always at risk of getting destroyed by disease and farmers are hard-pressed with declining yields. While the world’s population continues to grow, socio-economic behaviors are shifting as disposable income rises. Farmers are under immense pressure to meet the supply of rising demand, so they’re looking for innovative ways to increase production. 

Role of AI in commodity intelligence

Scratchpad notes, hours of obtaining and analysing market data no longer cut the chase. The rising volatility and unpredictability of commodities has made AI a key component of commodity intelligence. Agricultural practices need to be modernized to meet high demands. Forecasts aid farmers in risk management since production decisions are made before prices are determined. The availability of high-quality, reasonably priced food benefits consumers. Providing information on projected prices also aids in the fair operation of markets like ours. Prediction is also used to identify emerging issues and formulate policy responses.

Price Forecasting Web

Machine learning application

Machine learning is outlined jointly of the factitious intelligence applications that have evidenced to supply winning prediction models in numerous aspects, like the stock exchange, weather, business choices, and crop costs in our case. Crop price estimation and evaluation are done to take an intelligent decision before farming a specific type of crop. Eventually, the findings are displayed as an online application so farmers will simply access them.

Within the market, volatility and unpredictability in crop prices are foreseen. These price swings are mostly due to a scarcity of previous designs. This causes changes in demand as well as the market price of a crop. When the value rises, associate farmers incur an investment loss; when the value falls, the products are overpriced, creating a disadvantage for customers.

We provide smart recommendations to the stakeholders through better crop selection, access to market linkages, and knowledge-enabled tools to foster growth, along with an ecosystem that promotes growth. As we realize technology is not a single solution to this multifaceted problem, our prediction algorithm takes into consideration multiple micro and macro-level inputs specific to the type of crop. The data collected are often artifact costs, satellite pictures, coordinates of farms, etc. And with the appliance of IoT devices like sensors, data such as temperature, moisture, soil fertility, rainfall, etc.

A profitable crop value prediction system such as ours can provide farmers, traders, or agri stakeholders with an opportunity to gain profit in a much bigger context. Understanding and anticipating agricultural expenses using technology can greatly aid in making data-driven decisions and enhancing productivity.

The real credibility of our solution is that it will allow the farmer to make more informed decisions by looking at the recommendations based on real-time data forecasts given by our AI-driven algorithm. It aims to solve the problem of crop prices with more effective forecasts to secure farmers’ income.

Looking for ways to implement price prediction in your farm operations? Let’s connect!

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