A Survey on Smart Agriculture: Development Modes, Technologies, and Security and Privacy Challenges

Abstract

With the deep combination of both modern information technology and traditional agriculture, the era of agriculture 4.0, which takes the form of smart agriculture, has come. Smart agriculture provides solutions for agricultural intelligence and automation. However, information security issues cannot be ignored with the development of agriculture brought by modern information technology. In this paper, three typical development modes of smart agriculture (precision agriculture, facility agriculture, and order agriculture) are presented. Then, 7 key technologies and 11 key applications are derived from the above modes. Based on the above technologies and applications, 6 security and privacy countermeasures (authentication and access control, privacy-preserving, blockchain-based solutions for data integrity, cryptography and key management, physical countermeasures, and intrusion detection systems) are summarized and discussed. Moreover, the security challenges of smart agriculture are analyzed and organized into two aspects: 1) agricultural production, and 2) information technology. Most current research projects have not taken agricultural equipment as potential security threats. Therefore, we did some additional experiments based on solar insecticidal lamps Internet of Things, and the results indicate that agricultural equipment has an impact on agricultural security. Finally, more technologies (5G communication, fog computing, Internet of Everything, renewable energy management system, software defined network, virtual reality, augmented reality, and cyber security datasets for smart agriculture) are described as the future research directions of smart agriculture.

A Survey on Mobile Applications for Smart Agriculture

“…Smart agriculture refers to the incorporation of information and communication technologies into modern farming processes for improved management of farm activities [18,59,70]. In the literature, the terms agriculture 4.0 [84,88], facility agriculture [31,84], order agriculture [84], smart agriculture/farming [25,84], precision agriculture/farming [55,82], digital agriculture/farming [10], and intelligent agriculture/farming [84] have been used interchangeably. Other terms that have been used to refer to smart agriculture include [59]: (1) prescription farming, (2) farming-by-thefoot, (3) site-specific crop management, (4) satellite farming, and (5) precision livestock farming.…”

“…Overall, security and privacy issues are still a concern in all smart agriculture processes, since it has not been given much attention [84]. For instance, sending data to common cloud platforms, especially when using crowdsourcing techniques, may require end-users to share information that can be intercepted in cyber-security bridges.…”

An Overview of CAN-BUS Development, Utilization, and Future Potential in Serial Network Messaging for Off-Road Mobile Equipment

“…Local storage or cloud computing will be necessary to store and process the vast amount of data created by this potential technology [57]. Data processing on-board the vehicle, near the working equipment, is referred to as 'edge computing' [56,58]. It is highly probable that agricultural vehicles will eventually be able to perform a variety of complex, agronomic tasks from a preprogrammed routing structure, through the combined utilization of both IoT and EC technologies.…”

Model Predictive Control versus Traditional Relay Control in a High Energy Efficiency Greenhouse

“…On the contrary, due to the peculiar characteristics of the greenhouse site (the presence of a double aquifer at some 10 and 80-m depths, respectively) measured values of the carried liquid temperature, the ground side was demonstrated to be very constant in time, and this is the reason for setting it as a constant in the present model. In Equation ( 4), the estimated heat transfer coefficient of heat exchanger water/air in the AHU is considered; in fact, the decrease of water temperature T out i − T in i is proportional to the heat transferred to the air in the AHU heating coil Q i , evaluated as in Equation (7). Equation ( 5) is the definition of the performance parameter COP for the GCHP.…”

“…In this context, Agriculture 4.0 represents a great opportunity to take into account the variability and uncertainties involving the agri-food production chain, especially due to the costumers' inconstancy or in fighting emergency situations such as the impact of the COVID-19 pandemic [4]. The main innovative technologies able to support this transition include the Internet of Things (IoT) [5], Artificial Intelligence (AI) [6], remote sensing and new applications in intelligent control and the automation of production processes [7].…”