Abstract
Farmers use internet of things (IoT) devices to implement smart agriculture and optimize agricultural processes. This chapter identifies different types of IoT devices for smart agriculture. Then, advantages of using IoT-based smart agricultural systems are outlined. Subsequently, key issues to consider when deploying IoT for smart agriculture in developing countries are explored. Challenges such as limited number agricultural specialists, poor network infrastructure and internet connectivity, and farmers' inability to afford IoT devices are considered. Furthermore, techniques to use IoT systems to provide agricultural advisory services to smallholder farmers are discussed. Also, techniques to use IoT system for early detection of plant diseases are presented. Finally, based on the observations, recommendations are presented to promote the adoption of IoT solutions for agriculture in developing countries.
TopIntroduction
Internet of Things (IoT) systems provide mechanisms for data acquisition and communication infrastructure to connect smart devices to end-user applications through the Internet. The systems also provide mechanisms for cloud-based intelligent data analysis and process automation (Qureshi et al., 2022). These capabilities are useful in the field of agriculture. Farmers use IoT systems to implement smart agriculture, optimize agricultural processes, and increase production. Furthermore, IoT systems enable farmers to address various challenges that are related to crop health, soil nutrients, environmental conditions and climate change, plant diseases, control of agrochemicals, irrigation systems, etc. For example, farmers use IoT systems for soil monitoring to determine the nutrient status of soil so that measures can be taken accordingly when nutrient deficiencies are found. An IoT system that is enabled with Artificial Intelligence (AI) techniques can be used to implement an intelligent irrigation system that uses real-time data from the farm to prepare a watering plan and decide when to start or stop the sprinklers automatically. As a result, unnecessary use of water is prevented, and the irrigation process is optimized. To optimize the process of harvesting fruits, farmers use IoT systems to monitor fruit conditions such as color and size to predict an optimal harvest date. Table 1 presents examples of IoT systems that are used to address different challenges in agriculture.
Table 1. Examples of IoT systems to address different challenges in agriculture (Ayaz et al., 2019)
Challenge | Operation of IoT systems |
| Scarcity of groundwater for irrigation | IoT system obtains real-time data input from sensors embedded in a farm then it offers suggestions for watering management to farmer’s mobile devices to ensure efficient use of the available water. |
| Damage due to pests | IoT-based automated trap captures, counts, and characterizes insect types. Then, it uploads data to the cloud for detailed analysis. Farmers access the data and use it for pest control. |
| Losses due to crop diseases | IoT systems use information on climatic conditions to provide predictions and early detection of crop diseases. Rapid and accurate detection and diagnosis of diseases play a significant role in minimizing losses. |
| Soil degradation | IoT systems with AI techniques employ unmanned aerial vehicles and sensors to produce precise information for soil analysis. Farmers obtain accurate information about the status of soil and plan on techniques to improve the soil condition. |
| Unpredictable weather conditions | IoT systems use sensors to monitor the humidity, moisture level, temperature, etc. Also, detect rain and forecast floods or droughts to help farmers make informed decisions in challenging weather conditions. |
| Inefficient use of fertilizers | IoT systems employ AI algorithms and Nitrogen-Phosphorus-Potassium (NPK) sensors. Data from the NPK sensors is sent to a cloud server to support fast retrieval of data and detection of nutrient deficiencies. An alert message is sent to the farmer to inform about the appropriate quantity of fertilizer to be added to the field at right the time. Thus, agricultural advisory services are provided. |
Key Terms in this Chapter
Unmanned Aerial Vehicle: It is a robot that flies autonomously, and it can be guided by a remote control.
Internet of Things: A network of physical objects such as unmanned aerial vehicles, robots, and smartphones that are embedded with sensors, software, and other technologies to enable communication and exchanging of data between the devices over the Internet.
m-Agri services: The practice of using mobile devices such as mobile phones and tablet computers to provide agricultural advisory services to farmers.
Agricultural Robot: An automated machine that is designed for use in the agriculture industry. It executes specific agricultural tasks with little or no intervention from the farmer.
Smartphone: A mobile phone that functions as a portable computer. It has a touchscreen interface.
Sensor: A device that detects a physical parameter that occurs in its surrounding environment. The physical parameter can be in the form of temperature, humidity, light, or other forms. Sensor converts the parameter into data that human or machines can interpret.
Smartphone Application: A software application designed for use on a smartphone. It performs specific tasks.
Smart Agriculture: A farm management concept that employs Internet of Things systems at various levels and scales of agricultural production, enabling farmers to improve food production.