Internet of Things for the Future of Smart Agriculture: A Comprehensive Survey of Emerging Technologies Othmane Friha, Mohamed Amine Ferrag, Lei Shu, Senior Member, IEEE, Leandros Maglaras, Senior Member, IEEE, and Xiaochan Wang Abstract—This paper presents a comprehensive review of emerging technologies for the internet of things (IoT)-based smart agriculture. We begin by summarizing the existing surveys and describing emergent technologies for the agricultural IoT, such as unmanned aerial vehicles, wireless technologies, open-source IoT platforms, software defined networking (SDN), network function virtualization (NFV) technologies, cloud/fog computing, and middleware platforms. We also provide a classification of IoT applications for smart agriculture into seven categories: including smart monitoring, smart water management, agrochemicals applications, disease management, smart harvesting, supply chain management, and smart agricultural practices. Moreover, we provide a taxonomy and a side-by-side comparison of the state-of- the-art methods toward supply chain management based on the blockchain technology for agricultural IoTs. Furthermore, we present real projects that use most of the aforementioned technologies, which demonstrate their great performance in the field of smart agriculture. Finally, we highlight open research challenges and discuss possible future research directions for agricultural IoTs. Index Terms—Agricultural internet of things (IoT), internet of things (IoT), smart agriculture, smart farming, sustainable agriculture.   I. Introduction A GRICULTURE is the largest source of food in the world. It has been paramount to the development of civilizations throughout history. The United Nations (UN) estimates that by 2050, the world’s population will increase by 2 billion people from the current 7.8 billion, meaning the planet will need to support about 11 billion people by the end of the century [1]. As a result, the global demand for food and water will continue to increase. Agriculture is the world’s largest consumer of water, where it is used to support a wide range of activities such as irrigation, watering, and cleaning of livestock and aquaculture; using about 70% of the world’s annual water consumption [2]. These applications pollute water with high amounts of nutrients, pesticides, and other pollutants. It would appear that global food production has to increase to satisfy the world’s population growth. However, the Food and Agriculture Organization of the United Nations (FAO) believes that the challenges of hunger elimination and food security do not necessarily require an increase in agricultural production, even by 50% [3], if agricultural production systems become more sustainable [4]. Technology, research, and development must be used to the fullest extent possible, to realize the principles of sustainable agriculture. Throughout the history of agricultural development as shown in Fig. 1, there were four distinct revolutions, namely, 1) age of traditional agriculture featured by human and animal power, 2) age of mechanized agriculture featured by rumbling sounds, 3) age of automated agriculture featured by high- speed development, 4) age of smart agriculture featured by emerging technologies, as discussed by Liu et al. in [18], and Huang et al. in [19]. Therefore, smart farming offers a path to sustainability through the use of technology. It involves the use of information and communication technologies (ICTs) in the cyber-physical cycle of farm management, with techno- logies such as the IoT and cloud computing, robotics, and artificial intelligence (AI) [20]–[24]. Precision Agriculture is a smart farming approach that improves the accuracy of operations by giving each plant or animal precisely what it needs to grow in the best possible way, optimizing overall performance while reducing waste, inputs, and pollution. While precision agriculture is a very sophisticated technology, it only takes into account variables related to field conditions. On the other hand, smart farming goes further by making management duties based not only on geographical location Manuscript received September 20, 2020; revised November 25, 2020, December 27, 2020; accepted December 30, 2020. This work was supported in part by the Research Start-Up Fund for Talent Researcher of Nanjing Agricultural University (77H0603) and in part by the National Natural Science Foundation of China (62072248). Recommended by Associate Editor MengChu Zhou. (Corresponding author: Lei Shu.) Citation: O. Friha, M. A. Ferrag, L. Shu, L. Maglaras, and X. C. Wang, “Internet of things for the future of smart agriculture: A comprehensive survey of emerging technologies,” IEEE/CAA J. Autom. Sinica, vol. 8, no. 4, pp. 718–752, Apr. 2021. O. Friha is with the Networks and Systems Laboratory, University of Badji Mokhtar-Annaba, Annaba 23000, Algeria (e-mail: othmane.friha@univ- annaba.org). M. A. Ferrag is with the Department of Computer Science, Guelma University, Gulema 24000, Algeria (e-mail: ferrag.mohamedamine@univ- guelma.dz). Lei Shu is with the College of Engineering, Nanjing Agricultural University, Nanjing 210095, China, and also with the School of Engineering, University of Lincoln, Lincoln LN67TS, UK (e-mail: lei.shu@ieee.org). L. Maglaras is with the School of Computer Science and Informatics, De Montfort University, Leicester LE1 9BH, UK (e-mail: leandrosmag@gmail. com). X. C. Wang is with the Department of Electrical Engineering, Nanjing Agricultural University, Nanjing 210095, China (e-mail: wangxiaochan@njau. edu.cn). Color versions of one or more of the figures in this paper are available online at http://ieeexplore.ieee.org. Digital Object Identifier 10.1109/JAS.2021.1003925 718 IEEE/CAA JOURNAL OF AUTOMATICA SINICA, VOL. 8, NO. 4, APRIL 2021