Agriculture is the industry that accompanied the evolution of humanity from pre-historic times to modern days and fulfilled faithfully one of its most basic needs: food supply. Today this still remains its core mission, but it’s integrated in a more complex than ever mechanism driven by multiple sociological, economic and environmental forces.
This $5 trillion industry representing 10 percent of global consumer spending, 40 percent of employment and 30 percent of greenhouse gas emissions continues to keep pace with world’s evolution, changing tremendously over the past years. Digital and technological advancements are taking over the industry, enhancing food production while adding value to the entire farm-to-fork supply chain and helping it make use of natural resources more efficiently.
Data generated by sensors or agricultural drones collected at farms, on the field or during transportation offer a wealth of information about soil, seeds, livestock, crops, costs, farm equipment or the use of water and fertilizer. Internet of Things technologies and advanced analytics help farmers analyze real time data like weather, temperature, moisture, prices or GPS signals and provide insights on how to optimize and increase yield, improve farm planning, make smarter decisions about the level of resources needed, when and where to distribute them in order to prevent waste.
Efficiency and productivity will increase in the next years as ‘precision agriculture’ grows bigger and farms become smarter and more connected. It is estimated that by 2020, over 75 million agricultural IoT devices will be in use, while the average farm is expected to generate an average of 4.1 million data points every day in 2050, up from 190.000 in 2014.
While the growing number of connected devices represents a big opportunity for food and agribusiness players, it also adds more complexity for farmers and organizations. Moreover, the explosion of unstructured data, like social media posts, imagery or video content drives the need to know more, to receive real time recommendations on close at hand devices, like smartphones or tablets. The solution? The use of cognitive technologies that help understand, learn, reason, interact and thus, increase efficiency.
Here are five ways agriculture could benefit from these technologies:
- Help IoT achieve its maximum potential
While digital transformation is disrupting the agricultural world and more data comes feed the systems, solutions like the Watson IoT platform enhance value by applying machine learning abilities to sensor or drone data, transforming management systems in real artificial intelligence systems. Cognitive IoT technologies allow many types of correlations of large amount of structured and unstructured data from multiple sources, such as historic weather data, social media posts, research notes, soil information, market place information, images, etc., to extract knowledge and provide organizations with richer insights and recommendations to take action and improve yields.
- Image recognition and insight
Agricultural drones help already farmers scan fields, monitor crops and seeding or analyze plant health. Farm activities can become much more effective when drone data, IoT and computer vision technologies join forces to optimize strategies. Very recently, Aerialtronics, manufacturer of unmanned aircraft systems, partnered with IBM to bring the IBM Watson IoT Platform and the Visual Recognition APIs to commercial drones in order to capture images, analyze them in near-real time, identify areas of concern and take actions. These artificial intelligence systems will save time, increase safety and reduce potential human error while improving effectiveness. Agriculture could benefit greatly out of it.
- Skills and workforce
In its most recent World Urbanization Prospects report, UN predicts that, by 2050, 66% of the world’s population will live in urban areas. This growing urbanization will lead to a decrease of workforce in the rural areas. Innovative technologies using cognitive systems will help address this challenge by easing farmers’ work, removing the need for large numbers of people to work the land. Many operations will be done remotely, processes will be automated, risks will by identified and issues solved before occurring. Farmers will be able to take more informed and rapid decisions. In the future, the right mix of skills will probably increasingly be technology and agricultural skills rather than pure agricultural.
- Determine the best options to maximize return on crops
The use of cognitive technologies in agriculture could help determine the best crop choice or the best hybrid seed choices for a crop mix adapted to various objectives, conditions and better suited for farm’s needs. Watson can use diverse capabilities to understand how seeds react to different soil types, weather forecasts and local conditions. By analyzing and correlating information about weather, type of seeds, types of soil or infestations in a certain area, probability of diseases, data about what worked best, year to year outcomes, marketplace trends, prices or consumer needs, farmers can make decisions to maximize return on crops.
- Chatbots for farmers
Chatbots are conversational virtual assistants who automate interactions with end users. Artificial intelligence powered chatbots, using machine learning techniques, understand natural language and interact with users in a personalized way. While it’s still early days and chatbots are used mostly by retail, travel, media or insurance players, agriculture could also leverage this emerging technology by assisting farmers with answers to their questions, giving advice and recommendations on specific farm problems.
Although at the beginning, these ways of using cognitive technologies predict exciting times ahead for agriculture on its road towards efficiency, sustainability and meeting the world’s food needs. We’re looking forward to seeing how farmers, agribusinesses and other decision makers on the value chain will harness the power of IoT and artificial intelligence to shape the industry’s future.
Source: IBM Watson