Greetings, fellow Nawala! May you always be in good health.
This is the IAES Nawala of the Institute of Advanced Engineering and Science. Today we will share some news about smart farming. Smart farming is a technology that uses data to improve agricultural efficiency and productivity. It involves data collection and analysis, precision farming, automation, IoT, drones, farm management software, and environmental sustainability. This approach with technology is expected to increase crop yields and save costs. As expressed in his research Al-Khowarizmi (2022) related to smart farming on a farm using an information technology approach.
Al-Khowarizmi Al-Khowarizmi, Arif Ridho Lubis, Muharman Lubis, Romi Fadillah RahmatSmart farming in various worlds is not just about applying technology in terms of storing data on agricultural land. However, having a concept of measurable data based on available computational techniques trained and then generating knowledge. As an application, the agri drone sprayer can be used for the process of applying pesticides and liquid fertilizers on each side. In addition, drone surveillance is also useful in implementing smart farming such as mapping land so that farmers will know the condition of their agricultural land. However, the soil and weather sensor will also help the farmers to monitor the farmland as well. Devices with sensors can only obtain data in the form of air and soil humidity, temperature, soil pH, water content and forecasting the harvest period. So that the smart farming model can help farmers to get recommendations, in preventing the predicted damage to their land and crops. However, according to its geographical location, the application of smart farming can be a smart solution to agricultural problems in Indonesia and make the future of Indonesian Agriculture a technology-based smart agriculture.
Vertical farming is an agricultural method that optimizes the use of space by growing crops vertically. Tung Ng et al. (2023) introduced an IoT-based smart farming solution to monitor and manage vertical farming. Users can adjust soil moisture and provide ultraviolet light to plants. This solution can monitor in real-time, reduce energy consumption, increase flexibility, and improve sustainable and efficient food production.
Harn Tung Ng, Zhi Kean Tham, Nurul Amani Abdul Rahim, Ammar Wafiq Rohim, Wei Wen Looi, Nur Syazreen AhmadIn this paper, we present an internet of things (IoT) powered solution that facilitates effortless monitoring and management of vertical farming operations. Our proposed approach employs cost-effective embedded microcontrollers and sensors to keep a tab on crucial parameters like soil moisture, air humidity, and temperature. The data acquired from these sensors can be accessed through a web page that is compatible with all web browsers and smart gadgets such as mobile phones and tablets. Furthermore, the IoT platform offers users the ability to regulate soil moisture and administer ultraviolet light to plants. The system can bring many benefits such as enabling real-time monitoring and control of environmental conditions, reducing energy consumption, improving scalability and flexibility, and contributing to the sustainable and efficient production of food.
Smart farming is not limited to plants only, implementation in livestock or fisheries is also included. Like the research by Moutaouakil and Noureddine (2023), they made an application design to monitor livestock. The adoption of this system promises good results for intelligently transforming traditional cattle farming by reducing manual monitoring time and achieving good accuracy in early disease detection, automatic tracking of estrus cycles, and mapping the location of cows across farm fields.
Khalid El Moutaouakil, Noureddine FalihThe integration of technology in agriculture has led to the adoption of smart farming systems, which are becoming increasingly popular for optimizing resources, reducing labor costs, and improving efficiency. This article presents a design of a smart cattle monitoring farm system, which focuses on monitoring individual animal behavior and health, improving resource management, and optimizing overall farm efficiency. The proposed system integrates various internet of things (IoT) sensors, communication technologies, and cloud computing to provide a real-time monitoring solution for cattle farms. The system uses machine learning (ML) algorithms to analyze data on cattle behavior, health, and performance, which can be accessed through web and mobile applications by farmers to proactively monitor their herd. The adoption of the system promises good results for intelligently transforming traditional cattle farming by reducing manual monitoring time and achieving a good accuracy in early detection of diseases, automated tracking of estrus cycles, and location mapping of cattle across the farm fields.
Smart farming in fisheries is also called smart aquaculture. Smart aquaculture is developed using advanced technology to monitor, manage, and improve fish production. The application of environmental monitoring systems, automatic feeding, data analysis, and efficient water management help to improve the sustainability of smart aquaculture operations. Al-Mutairi and Al-Aubidy (2023) in their research showed that the fisheries approach combined with smart farming achieved the best performance of real-time monitoring and control systems in fish ponds.
Abdallah Waddah Al-Mutairi, Kasim Mousa Al-AubidyFish farming is still controlled and managed in the traditional way where water quality and fish feeding are manually controlled. There is a need to use computer and communication technology in fish farms for remote monitoring and control. This paper deals with the design and implementation of an internet of things (IoT) based system for real-time monitoring, control and management of fish farming. The design of such a system is based on measuring different types of variables and using the information to control fish growth and increase productivity. Each fish pond is a node in a wireless sensor network. The node contains an embedded microcontroller connected to a set of sensors and actuators and a wireless communication module. Two fuzzy controllers are designed to control the water quality in the ponds as well as the environment using five sensors in each pond plus three environmental sensors. Practical results indicate the accuracy of the measurement system compared to the results obtained from commercial devices used on the farm. These results also showed that the proposed approach achieves the best performance of the real-time monitoring and control system in fish ponds.
The above articles are a small part of the research on smart farming. To get more information, readers can visit the page and read articles for FREE through the following links: https://ijai.iaescore.com/, https://ijres.iaescore.com/, https://ijeecs.iaescore.com/, and https://beei.org/.
By: I. Busthomi