For precision framing to be effective, various factors should work accurately. Some of the factors include the appropriate machine status, crop behavior, light, temperature, humidity, soil composition, and weather among many others. The information about all the factors is obtained using satellites, drones, GPS, APIs, and sensors, and is useful at diverse levels including:
- Efficiency in farming depends on the accuracy of the decisions taken. With the IoT, it is possible to collect real-time data for the purpose of helping farmers in making smart and ad-hoc decisions that step from observed threats or opportunities in the farmland.
- The statistical data obtained from any farmland is important in making historical analysis of the parcel of land. Such an approach can be useful in making predictions about the preferred crops, and the level of yields to expect.
Precision farming requires effective interconnection of objects such as cameras and sensors for the extraction of local data that can be used in Big Data, as well as analytics tools used in storing huge data obtained from the farm, have it processed and turned into information that can be used in improving the farming practice. Additionally, it is important to integrate all the services from any one given component to form structured as well as well-organized orchestrations.
Precision farming does not only aim at the simple generation of data through sensors, but also in the analysis of the data for evaluating the required actions. IoT can be successfully applied in smart farming especially in area such as storage monitoring, field observation, and farm vehicle tracking. Such approaches are important in that they give farmers reliable data on the condition of the crops.
The future of agriculture is bright with the adoption precision farming. However, without effective IoT solutions, it can be hard to achieve the goals and objectives of smart agriculture