IoT solutions for smart farming: A comprehensive review on the current trends, challenges and future prospects for sustainable agriculture - Duc Ha, Chu; Duc Chien, Le; Truong Trinh, Phung; Van Tien, Tran; Phuong Thu, Pham; Tien Dung, Le; Minh Trien, Pham (Journal of Forestry Science and Technology, 2023)
Agriculture is the most resource-intensive human activity. The goal to reduce agricultural input while producing more has been a primary driver of agricultural technology advancement since its inception. With recent advancements in supporting technologies, the usage of Internet-of-things (IoT) has become a trend in farming practice for agriculture management that use information technology to ensure that soil and plants receive their requirements for optimum health and productivity. It could be significant to summarize the trends and challenges of the application of IoT-based solutions in precision agriculture, more specifically smart crop production. Thus, the current review sought to give a complete overview of the use of IoT technology in smart farming. By surveying recent high-quality publications, IoT-based solutions applied to smart farming, with four basic layers, including data collection (perception), data transmission (transport), data processing, and application layers were summarized. The use of IoT solutions allows for resolving several issues in smart farming, such as the optimization of input resources, saving irrigation water, reducing the amount of fertilizer and pesticides, and optimizing energy resources. Accordingly, we discussed some notes about sensors, microcontroller systems, communication methods, and cloud platforms. In particular, a list of low-cost sensors and several typical single-board computers was provided. The IoT communication was discussed to get insight into the essential considerations. Since then, several key points have been noted for further directions of the application of IoT-based solutions for smart farming. Taken together, our mini-review could provide solid information for further construction and development of smart models of farming.