The three previous industrial revolutions profoundly transformed agriculture industry from indigenous farming to mechanized farming and recent precision agriculture. Industrial farming paradigm greatly improves productivity, but a number of challenges have gradually emerged, which have exacerbated in recent years. Industry 4.0 is expected to reshape the agriculture industry once again and promote the fourth agricultural revolution. In this paper, first, we review the current status of industrial agriculture along with lessons learned from industrialized agricultural production patterns, industrialized agricultural production processes, and the industrialized agri-food supply chain. Furthermore, five emerging technologies, namely, the Internet of Things, robotics, Artificial Intelligence, big data analytics, and blockchain, toward Agriculture 4.0 are discussed. Specifically, we focus on the key applications of these emerging technologies in the agricultural sector and corresponding research challenges. This paper aims to open up new research opportunities for readers, particularly industrial practitioners.

The connectivity and intelligence of Internet of Things (IoT) equipment offer improved services, but several technical challenges have emerged in recent years that hinder the widespread application of IoT, e.g., security and safety. Cyber-security and privacy countermeasures are widely used in IoT equipment, and many studies have been conducted. However, an important aspect that is often overlooked in security literature is IoT equipment’s physical security and safety, namely, preventing IoT equipment from vandalism and theft. Therefore, this article provides an overview of IoT equipment’s physical security and safety to draw attention to new research opportunities in this area. Afterward, we discuss, among other aspects, antitheft and antivandalism schemes along with circuit and system design, additional sensing devices, biometry and behavior analysis, and tracking methods. Besides, we summarize the artificial intelligence solutions for the physical security and safety of IoT equipment. Finally, we conclude with four future research opportunities.

In the future, agriculture will face the need for increasing production, sustainability, wisdom, and efficiency, which will bring significant challenges to the development of modern agriculture. With the gradual popularization of 5G, advanced information technologies such as the Internet of Things and artificial intelligence promoted the evolution of modern agriculture to intelligent agriculture. The 5G-based Internet of Things will play an essential role in the development of smart agriculture. This paper investigates the research progress of 5G Internet of Things in smart agriculture. It sorts out the development status of 5G smart agriculture Internet of Things in recent years. Following that, the concept of 5G smart agriculture Internet of Things is put forward. It expounds on the connotation, architecture, and enabling key technologies. According to the key application scenarios of smart agriculture, practical cases are presented, the development trend and application value of 5G smart agriculture Internet of Things are shown, and the future development direction is put forward. Firstly, the concept of smart agriculture is distinguished, and the category scenarios of smart agriculture are summarized. Following that, the current review research on 5G-IoT is analyzed. This paper focuses on the analysis and summary of the changes brought by 5G to various key scenarios in smart agriculture. This paper analyzes the related key technologies and challenges, puts forward some key scientific problems, and summarizes the research ideas. Finally, the development trend and application value of 5G smart agriculture Internet of Things are shown. The future development direction is also proposed.

The rapid development of the agricultural Internet of Things (IoT) is inseparable from the support of wireless sensor networks (WSNs) in recent years. To further facilitate the adaptation of WSNs to agricultural applications, reducing the energy consumption of sensor nodes in agricultural environments has become a crucial problem. Sleep scheduling in randomly deployed WSNs is an effective method to reduce the energy consumption of sensor nodes, which can extend the network lifetime while ensuring network coverage. However, most of the existing sleep scheduling algorithms require frequent information exchange (such as broadcasting to find neighboring nodes and collecting nodes’ residual energy), which will inevitably lead to massive energy consumption. To address this problem, in this article, an unmanned aerial vehicle (UAV)-assisted sleep scheduling algorithm (UAVSS) is proposed, which avoids excessive information exchange among nodes and ensures sufficient network coverage with the least number of sensor nodes. The UAV traverses all the sensor nodes along the shortest path to help information exchange and gather sensing data. Furthermore, the UAV path is planned by using the latest monarch butterfly optimization (MBO) algorithm. Simulation results indicate that the proposed UAVSS can prolong the network lifetime while ensuring the required area coverage.

Wound healing is a significant problem in clinical management. Various functional dressings are studied to promote wound healing through biochemical factors. They are generally expensive, complex to fabricate, and may adversely affect the wound. Mechanical forces are the critical regulators of tissue repair. Although contraction is shown to promote wound healing, the underlying mechanisms are not fully understood. In this study, a novel adhesive temperature‐sensitive mechanically active hydrogel with a simple and inexpensive preparation process is developed. The dressing is able to adhere to the wound surface and actively contract the wound in response to body temperature. This mechanical contraction enhances the proliferative activity of basal cells, reduces the inflammatory response of the wound, and promotes wound healing. Furthermore, RNA‐seq clarifies how the gene regulatory network is regulated by contraction. Finally, using pharmacological inhibitors, YAP and MEK are identified as the key signaling molecules for contraction‐mediated tissue healing in vivo.

Solar Insecticide Lamp (SIL) is a green prevention and control technology for pests. As the development of Wireless Sensor Networks (WSNs), the combination of SILs and WSNs forms a novel agricultural Internet of Things -Solar Insecticide Lamp Internet of Things (SIL-IoT). However, the complex geographical characteristic of actual farmland has a great impact on SIL deployment. In this paper, we study the SIL Deployment Problem (SILDP) with characteristics of full coverage, penetrable obstacles, irregular boundary and partition structure. According to partition structure caused by natural physiognomy feature, the actual farmland is divided into many subareas by ridges, and each subarea can be considered as a separate partition. Then, we formulate the SILDP in the scenario with partition structure as the quadratic assignment problem. After that, we propose two deployment methods based on genetic algorithm to address the SILDP. These two methods are the same in optimization objectives, but different in deployment sequence. Experimental results show that the proposed deployment methods equips better performance in terms of deployment cost compared with the other six peer algorithms.