In recent years, modern technologies, communications, cloud data, robotics, sensors, and automation systems have been actively introduced in agriculture, leading to the ubiquity of precision or smart farming. Like any other modern business, farms need relevant and accurate information.
Today, digital smart farming technologies can help end poverty and hunger faster, especially in developing countries, which mostly live off agriculture. In particular, the use of smartphones by farmers to access real-time farm information could significantly change the way the agricultural and food industries operate.
But how does all this information become accessible through a cell phone? Thanks to innovative farm software like Crop Monitoring by EOS Data Analytics that offers already collected and analyzed data in one place. But the force behind these opportunities is big data – a technology that allows for substantial data volumes collection and analysis based on advanced algorithms.
Why is Big Data Needed in Agriculture?
Innovations in agriculture help farmers increase their yields and incomes by switching to locally appropriate seeds and fertilizers, smart plant protection against diseases and pests, adapting to climate change, accessing financial services, and selling products at the best price.
Moreover, the use of robotic agricultural equipment in the fields, equipped with systems that perform mathematical calculations based on AI, can increase and improve yields, reduce costs, and increase agricultural procedures’ safety.
Most investments that flow into the agricultural sector also concern big data and analytics, food safety and traceability, biotechnology, optimization hardware, sensors, and communication facilities. These technologies are expected to develop at a tremendous speed since now people have capabilities that did not exist a decade ago: access to the Internet, smartphones, tablets, cloud storage, drones, etc.
How Farming Utilizes Big Data
Thanks to developments in big data, artificial intelligence, and machine learning, there is almost no need for human intervention when it comes to information collection and analysis. Special devices collect various data from the fields. For example, these devices need to be inserted into the ground to determine the moisture and other parameters of the soil. Others are attached to field equipment to monitor their route, performance, and fuel.
There are also weather stations for weather forecasting, services for obtaining satellite images of fields, and drones for mapping the field and assessing the state of the crop through aerial monitoring.
Advanced software collects the resulting data, processes. It analyzes and provides farmers with valuable information in an accessible format to back up their decision-making with the most precise and relevant information.
Some technologies do not require any devices installed on the field at all. The software collects data from open sources such as open government databases or from satellite imagery. It analyzes it with advanced algorithms to pull out the necessary data the farmer may need.
What is Smart Farming?
Smart agriculture is a concept of agricultural activities based on introducing new technologies into standard farming practices. The technologies include IoT, sensors, UAVs, GPS, satellites, automation systems, etc. The purpose of using this tech is to optimize the production process while increasing yields and reducing costs.
Big Data in Food Processing
After the harvest, the produce undergoes several stages of handling: processing (cleaning up the product and removing damaged parts), quality assessment, packaging, and storage. Processes automated with the help of technologies based on big data, artificial intelligence, and the Internet of Things helps make sure that the product is being handled correctly at each stage and is not mismanaged. This allows for significantly reducing food waste.
For instance, different sensors can be used to track temperature, humidity, levels of oxygen, carbon dioxide, etc. d at all times so that as many products as possible can leave the farm in the best state, ready for sale.
As for food market players, they can use this information to determine the cause of the quality problems of the supplied products and avoid them in the future. But big data in the food industry is used not just in supply and quality control. Restaurant chefs, for example, can optimize prices on a menu and improve it based on customer preferences thanks to big data analysis.
Technologies have evolved, become cheaper, and advanced to such a level that it has become possible to obtain data on each agricultural facility and its surroundings, calculate algorithms of actions accurately, and predict the result with high precision for the first time in the industry.
Digitalization and automation of the maximum number of agricultural processes is now a globally recognized need in the development strategy of the world’s largest agro-industrial and food companies.
Big data collection and management systems are becoming an essential resource for further growth in agricultural productivity, ensuring a stable result and increasing competitiveness on a local and global scale.
Ultimately, the future of farming is currently impossible to imagine without big data that Local Digital Business provides used to maximize operational efficiency and minimize labor costs. Be it ground devices, satellite imagery, drones, or any other tech that utilizes data collection and analytics.