Keywords

Introduction

Agriculture is most countries’ principal factor of income and plays a critical role in their economic development. Different styles of agriculture are performed all over the world, with the goal of healthy food production to feed the world’s population. Agriculture is a developing country’s primary source of revenue. Modern farming began around the eighteenth century, during the British Agricultural Revolution, when numerous improvements to farming were accomplished in a little time, resulting in a productive increase in yield and more efficient ways. Food production must be raised swiftly to keep up with the rapid growth of the global population. Traditional farming practices result in irregular output, resource overuse and trash creation that is unchecked. Farmers will require more advanced technology to meet these demands, which will allow them to produce more while requiring manually less labour. This is when automation enters the picture. In this context, the introduction of 5G communications provides a potentially disruptive factor. In terms of communication, 5G’s enhanced data rate, less end-to-end latency and wider coverage have the ability to meet even the ever-increasing demand of IoT end users (Heidari et al. 2021). Its ability to accommodate a massive number of devices allows for the creation of a truly global Internet of Things. Furthermore, as it focuses on the integration of access methods, 5G could serve as a unified interconnection framework, allowing “things” to connect to the Internet seamlessly. The purpose of this study is to examine in depth the potential of 5G for the Internet of Things for reaping full benefits of smart farming. With machine-to-machine services, however, the adoption of 5G will assist speed up the complete procedure. The real-time data transfer capabilities of 5G can aid in the efficient operation of these technologies, allowing for quick, reliable, data-driven and real-time decision-making. Applications of 5G in agriculture include AI-enhanced machinery, drone sprayers, accurate harvest estimation, effective irrigation and livestock tracking as well as management (Tang et al. 2021).

Challenges Faced by Existing Network Technologies

The 4G networking paradigm faces significant restrictions that may restrain the technology from reaching its full prospective in the agriculture industry. One of the most significant limits is the operating area. Remote locations are not covered by existing wireless networks. Due to variable data rates, resource allotment, handoff and channel state, issues between heterogeneous networks facilitating QoS (Tong et al. 2019) networks poses a considerable challenge. The large number of antennae and transmitters causes poor battery life in mobile nodes. Because many current agricultural gadgets, such as drones and agribots are powered by battery, these cannot be incorporated in remote crop fields for long periods of time. Several devices are continuously rising in number, requiring greater intelligence, scalability, processing capacity, secure communication, etc., to conduct profound computational operations. Ultralow latency along with high connection is essential for IoT devices to deliver quick performance and low prices. Because it only permits IP-based packet switching connectivity, the existing 4G network (LTE) cannot provide such functionalities (Martin et al. 2011). Transitioning to next-generation 5G will address these limitations of previous generations.

Motivation of the Work

Farmers can expect the following benefits in the near future as a result of 5G’s accessible capabilities like faster communication where 5G will offer a data speed of up to 10 Gbps, which is 100 times faster than its predecessor, 4G. Real-time communication between stakeholders will be facilitated by faster speeds and much lower latency. Machine-to-machine data transfer will facilitate direct information transfer between 5G-enabled equipment without the need for human intervention that can improve agricultural processes’ speed and efficiency. 5G will reduce the costs where farm owners can significantly boost revenue by requiring less agri-inputs, labour and other resources. It’s possible that 5G will take longer to fully expand out and cover all distant locations. When it happens, though, this new agricultural technology will cut labour requirements while bringing automation. The 5G network minimizes the per unit time for data transfer, supports larger data rate, ensure secure and dependable connections required for efficiency of time-sensitive applications like irrigation scheduling which is dependent on real-time prediction of droughts and floods.

Existing Problems and Contribution

As 5G coverage spreads over the world, it will provide extensive coverage for numerous new applications. The 5G energy network uses LTE for both machines (LTE-M) and narrowband IoT technologies (Heidari et al. 2021). To meet service requirements, the 5G will form an extensively dense network. The high density creates a mobility organization difficulty and causes larger energy utilization. Energy harvesting methods help to deploy a large number of wireless sensors in both urban and rural locations. Intelligence is also added that will result in substantial energy savings during transmission. The ideal parameter settings to minimize energy loss can be attained via advanced analytics of network data (Tang et al. 2021). Furthermore, rather than the traditional reactive approach to energy management, a proactive method may be established. For a stable 5G future, we studied energy management and harvesting solutions for IoT devices. Based on energy harvesting schemes, IoT devices will be power conserving and management strategies at the circuit, system and device levels that will be implemented in the near future.

Scope of 5G-Enabled Networks in AgriIoT

5G provides a diverse set of capabilities to fulfil the needs of eMBB, mMTC and URLLC services. The notion of “network slicing” allows for the operation of many dedicated networks on a single platform. The flexibility of 5G specifications to dedicate a dedicated slice of the network for certain application areas will also enable new distant and mobile IoT applications, unlike earlier generations of mobile networks. In 5G, network slicing allows for various connection segments to be used to implement one or more use cases. In 5G, network slicing allows for various connection segments to be used to implement one or more use cases. The 5G network will be connected by a large number of IoT nodes. This will make ultra-reliable or ultra-low rate of time consumed for data transfer and communications possible (GSMA 2019). Edge computing and Artificial Intelligence at the edge, incorporating 5G, will perform novel augmented reality (AR), time-critical industrial IoT applications, virtual reality (VR), etc. The VR eye tracking interphase, that shows the user’s focal point and supplies images of high resolution at the point of focal plane, is an application area of VR-IoT. To save energy, reduced resolution is used elsewhere. 5G can provide accommodation to millions of 5G devices in a square kilometres because of its capability for “large machine type communication.” 5G technology is ideally suited to meet the reduced timing requirement to perform data transfer and dependability needs of crucial IoT equipments. The ability to deliver services for important and dependable systems, like agriculture monitoring based on real-time weather parameter sensing is critical to 5G with cellular networks. URLLC is a primary characteristic of 5G and one of its main foundation stones. URLLC IoT is utilized to better control traffic and prevent congestion while providing users with early warnings (Foerster et al. 2020). The majority of 5G IoT devices will be power-driven entirely by batteries. So, extending the network lifetime of IoT devices requires an energy-conserving plan like modifying the frequency of sensing and data collection. Low-cost ubiquitous computing is a major IoT enabler to ensure energy efficiency. The size of unit computing has shrunk over the last five decades, and this, together with new 5G network technologies like massive MIMO and millimetre-wave transmission, can help IoT realize its full potential. The reduction in accessible energy is the shortcoming of ubiquitous computing. Over time, the size of a single processing unit has shrunk dramatically. In the meantime, battery and energy storage technologies are progressing very slowly (Sen et al. 2018). As a result, the IoT nodes have a limited quantity of energy available. The sensors have a battery size which is modest. Because battery life is typically significantly shorter than electronic lifespan, developing an energy harvesting-based system that can achieve net-zero energy for sensor nodes will be a superior strategy.

Energy Consumption Management Methods in 5G Networks

Energy Harvesting technologies will be critical in extending network lifetime by providing a controlled manner of recharging batteries. It is a potential advancement which does not lessen the power requirement of devices but rather makes it easier to convert to self-powering in the event of a power outage. The 5G energy harvesting system can be divided into energy sources, energy conversion methods, energy harvesting phases, harvesting models, etc. Transducers can convert energy harvesting sources to usable electrical power that performs power conversion and energy storage capacity, such as supercapacitors or batteries, to store converted power. There are a variety of ambient energy sources available in the environment (Lee et al. 2018) like Solar, electromagnetic, mechanical vibrations or kinetic energy sources, thermal etc. are all examples of renewable energy sources. In general, electromagnetic radiation can be used to generate energy non-radiatively and radiative methods. The non-radiative method has a higher competence but less range, but the radiative method has an inferior efficiency but a comparatively better range. As a result, in the 5G and beyond future, effective utilization of these approaches is critical. Solar energy has already been shown to be a practicable source of significant power generation. Generators convert the mechanical energy into useful electrical power from there. Using a thermoelectric generator, energy is quickly extracted using thermal energy harvesting. Kinetic energy sources could be a critical enabler in the development of 5G-enabled components. With its speedy connectivity, 5G wireless capabilities may open up new options for agriculture-related data analytics (Yuan et al. 2020). If a generic power management framework can serve all 5G IoT devices with energy harvesting capabilities, the field’s extendibility is limited in which intelligent power management is required. The ability to stop a system while it is not in use is arguably the most efficient way to save energy. Sensors, power management, communication transceivers and energy harvesters make up the sensing nodes of IoT devices. The most practical way for reducing the system’s energy usage is to use the sleep mode to turn the BS on and off. This guarantees that the captured energy is used efficiently. Because their subsystems stay active in the idle state, 5G IoT devices may then also exhaust a large amount of energy when they are not transmitting data/sensing. Meanwhile, one of the aspects of next-generation networks is energy proportionality with traffic. Each BS sleep level is defined by a transition latency threshold. The sum of the part’s reactivation and deactivation latencies is the subcomponent transition rate of data transferred per unit time. When the BS is in sleep state, a quick activation time is used to keep subcomponents with a long transition rate of data transfer per unit time always active. In most current systems, this strategy is employed to preserve QoS. Utilizing the IoT device hardware capability, the network’s flexibility and the measurement periodicity acquired by the device, the sleep state can achieve noteworthy energy savings. The shortest BS sleep period is in sleep mode one (Debaillie et al. 2015). A BS that is in sleep mode 1 is still active and can receive data. When a BS is not transmitting data, it automatically switches to this sleep state. Sleep mode two denotes a middle-state sleep situation in which more subparts are deactivated, and it equates to 1 ms. Finally, the BS is in standby mode in sleep mode four, which lasts for a minimum of 1 s. In sleep mode 4, the BS is disabled, although it can be reactivated. The data transfer of IoT components can be scheduled with the four separate BS sleep modes to ensure that the energy harvested is used while still meeting QoS. For the 5G frame structure, five distinct numerologies have been established. Because of its high power density and efficiency, Lithium batteries can provide a long battery life. Massive IoT applications necessitate miniaturized and autonomous devices, restraining power management and energy storage ability. Non-rechargeable batteries will also be limited in their usage as a key energy source for vast IoT applications due to frequent replacement, environmental consequences and a shortage of energy sources. Another battery technology is solid-state thin film, which has a high energy concentration but low power density. Because of properties like bendability and manufacture in IC packages, these batteries enable significant size and cost reduction. Nowadays, supercapacitors are used in place of rechargeable batteries as it has an unconstrained charge–discharge cycle (Somov and Giaffreda 2015). Because batteries can be moulded into a variety of shapes and sizes, they remain a viable option for large-scale IoT deployments that require extremely low power consumption and a 10-year lifespan. Integrating rechargeable batteries with energy-conserving approaches is crucial to extend the lifespan of the 5G-enabled devices by recharging the batteries.

Application Areas of 5G in Smart Farming

Data Aggregation

For centralized data aggregation in large farming operations, 5G technology holds a lot of potential. To aggregate data from micro-monitored crop management systems, a large corporate farm may construct a private 5G network. These systems incorporate soil moisture sensor density that is hundreds of times greater than what is currently supported by available technologies. This network could allow for a more efficient real-time monitoring system, complete with triggers for limiting irrigation and other crop support systems (Xu et al. 2017).

Predictive Analytics

Large industrial farms can better utilize predictive analytics thanks to 5G technology, which enables data aggregation. Analytics software develops models and forecasts based on past and current data on circumstances (e.g. soil moisture and pesticide use) to assist farmers in making decisions. Analytics will become more exact as 5G enables denser real-time data, maximizing farm production and efficiency (Sevgican et al. 2020).

Drone Operations

Drones are increasingly being used by farmers to check their crops. Drones are less expensive than driving tractors through fields, and they provide more precise data on crop damage and other aspects. Drones will be able to collect higher-quality video data and transmit it faster thanks to 5G’s high-bandwidth technology. These high-speed data transfer capabilities will allow for the development of AI drone technology and real-time reports (Tang et al. 2021).

Animal Tracking and Real-Time Monitoring

Animal monitoring sensors will most likely remain connected through Wi-Fi, Bluetooth or LTE LPWAN Until Rel 17 increases the practicality of 5G low-power and denser sensor networks. Large concentrated farms, where 5G infrastructure can be installed across a small area (e.g. a chicken farm) and individual animals may be tracked, are an exception. Herd management sensors, such as smart collars and ear tags, have been developed by agricultural technology developers to track an animal’s position and health. An automated remedial action can be triggered based on any variation in these variables in order to preserve the typical circumstances for crop yield. Sensor data obtained for agriculture practices are in various forms depending on the precision and compatibility will necessitate the use of the relevant interfaces. To cover minimal or maximal distances, communication protocols are very important in IoT-based smart irrigation practices. Short ranges are covered by ZigBee or Wi-Fi, whereas to cover long ranges LoRaWAN, LPWAN protocols and Bluetooth are used. Narrowband IoT and long-term evolution of machine-type communications (GSMA 2019) are paving the way for 5G integration in the future and will have a significant impact on smart farming in the next years. The sensors must have maximal-range communication and should be energy-saving (Yao and Bian 2019). As a result, the sensors’ lifetime is significantly extended by transferring data at reduced energy and eliminating data repetition. 5G NR improves network energy performance and decreases interference by allowing adaptive bandwidth switching from lower to higher bandwidth, while interworking and LTE coexistence allow existing cellular networks to be used while still accommodating future evolution.

Autonomous Agriculture Vehicles

Farm tools will benefit from the development of autonomous vehicle technology in other industries. Tractors with onboard computers already allow operators to regulate minute details of farming tasks. Farm equipment that is self-driving will improve, allowing farmers to have more flexibility and efficiency while also saving money on labour. IoT sensor benefits can also be reaped by trucks used for crop transportation. These sensors can monitor cargo temperature and inform you if it gets too hot or cold. High-latency technologies like LPWAN will likely continue to be used by small mobile sensors like asset trackers. 5G will allow autonomous vehicles to send and receive larger, ultra-low-latency data streams, including videos using more powerful onboard computers (Tang et al. 2021).

Weather Stations

Farming operations are at the mercy of the weather. Large sections of crops can be lost due to illnesses and damage that can be avoided. Farmers can tackle this problem by using connected weather stations in the field to provide data on agricultural conditions. The InField monitoring system, designed by AMA Instruments, is one example. InField monitors soil moisture and texture, air temperature, wind speed and exposure to the sun. Weather stations in remote locations will very certainly continue to use LPWAN connectivity in the near future. 5G will help them because it will allow for more data-dense observation and edge computing. Smart farming will continue to grow as the cellular-connected world switches to 5G. Farmers will be able to make better decisions based on data and predictive analytics, resulting in increased productivity and efficiency (Tang et al. 2021).

5G Enabled Components in Agriculture

To implement seamless farming practices 5G enabled the use of a number of components as summarized below.

Drones and Unmanned Aerial Vehicles (UAVs)

UAVs can boost crop yields, save time and maximize long-term performance. These drones can be utilized for a variety of purposes. Both aircraft and ground-based missions are possible. Drones are helpful for doing quick and effective livestock monitoring (Vayssade et al. 2019). Farmers may fly a drone across a long distance using 5G technology (Faraci et al. 2018). In comparison to previous-generation mobile networks, the 5G network allows farmers to get real-time data as well as other critical sensory data faster. Drones do not utilize a lot of processing power, and all the data can be transferred to the cloud. Multiple drones (Razaak et al. 2019) can interact with one another to provide coordinated autonomous flight to perform several tasks with least energy expenditure, allowing for extended sensing time and economic operations. For decision-making, a large volume of data can be kept and processed. Drones can fly to supply agricultural products using 5G network’s vast network coverage and steady connection. The 5G cellular network combines with drone traffic supervision technologies to improve operations’ high-quality connectivity. Since, there is a large amount of data to be transferred, a data link with maximal rate of data transfer per unit time is needed, which is provided by robust 5G network coverage. Figure 6.1 shows applications of Unmanned Aerial Vehicles (UAVs) in Agriculture using 5G.

Fig. 6.1
An infographic of applications of U A V in 5 G-enabled agriculture includes scouting land and crops, soil and field analysis, seed planting, livestock monitoring, crop spraying, and health assessment.

Applications of unmanned aerial vehicles (UAVs) in the field of agriculture using 5G

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Virtual Consultation and Predictive Maintenance

Virtual consultation allows session services to attend to the requirements of farmers. Domain experts can straightforwardly derive a live streaming in real-time using sensors to obtain thorough views regarding condition and provide farmers solution for the improvement of agriculture and irrigation practice. Precision agriculture, soil sampling, disease management and animal health monitoring are some of the services provided by consultation services. Multiple machineries can be monitored in real time with 5G having fast transmission speed and low latency to monitor in advance and give repairs on time without any interruption. Using several sensors to monitor a huge number of weather conditions in real time, 5G will provide a new maintenance paradigm called advanced predictive maintenance. Based on feedback, the farmer is alerted of any forthcoming issues and any weakening parts, allowing repairs to be planned at suitable time rather than postponing any operations (Compare et al. 2020). This can drastically diminish unintended downtime caused by defective apparatus or machine malfunction.

Augmented and Virtual Reality

Farmers can benefit from augmented reality (AR) and virtual reality (VR) equipments in a diversity of ways. Through wearable glasses and smartphones, AR can provide diversities of information such as crop, animal and machinery statistics, soil and weather pattern changes, disease exposure for livestock, land examination and more (Garzón et al. 2020). The farmers can acquire important information like if the crops are unwell or when they can be reaped or sown using AR glasses. So, farmers can cultivate in a more efficient way to potentially lessen labour and ensure timely delivery while ensuring a premium quality harvest. Virtual reality can be utilized for immersive agriculture training and practice (Wang et al. 2014). An interactive VR experience increases the connectivity requirements even further. By offering realistic and powerful experiences for learners, 5G will enable online interactive learning taking maximum benefit from augmented reality and virtual reality over conventional offline education.

Agriculture Robots

The collaboration of AI and 5G exposes new advantages in live video monitoring, remote diagnostics, as well as the stabilization of drones and robots using precise parameter management. AI in agriculture is budding on a continuous rate to give modern solutions for enhancing crop yield and AI-powered robots are ready to revolutionize the industry. Recently, agricultural robots have been used to autonomously plant a variety of crops across large areas of land. Robots are designed to plot a route themselves all through the Machine vision is a core potential, allowing them to perceive, identify, confine and implement intelligent actions on plants. To avoid collisions, laser rangefinder is used to detect impediments in the robot’s pathway (Ramin Shamshiri et al. 2018). The robot can plot a route to its surroundings and be directed from any location utilizing cloud computation and a noteworthy amount of data is sent via 5G. Transmission of real-time photos recorded from sensors with super low latency via 5G network (Aijaz et al. 2017).

Cloud-Based Data Analytics

Data is one of the most significant aspects that are developing the smart agricultural business forward. On numerous farms, all the data acquired from sources like sensors and drones, are saved in cloud. 5G and edge computing allows data transfers to the cloud, allowing real-time analytics to help automate the farming process. Larger data must be transported to the cloud and then returned to users. To reduce complexity, cloud-based edge computing is mostly employed in smart robots. The cloud can be utilized as a data centre or a host for storing robot navigation and data processing control services. In the precision agriculture scenario, intelligence analyses these data in real time to develop AI for protective drones or machineries. By placing the GPU on the edge server, the need for the robot’s graphics processing unit (GPU) is eliminated. Because the data processing bandwidth is so high, only 5G can handle it. The robots’ physical size, power expenditure and cost have all been decreased dramatically. Over existing cell networks, 5G will vastly improve the data transfer experience. A huge volume of data may be successfully sent across several devices while minimizing data loss, reducing connection downtime and avoiding retransmission of data that consumes much time while transmitting a large number of data unnecessarily. Cloud computing provides faster data acquisition, transmission and processing at the cloud with minimal round transfer latency between various 5G devices, enabling maximum efficiency for sustainable agriculture management (Song, et al. 2019). Sensors, drones, robotics and smart devices, are the usage of 5G. There are several 5G characteristics like device density, ultra-low rate of data transfer per unit time, ultra-reliability and security. Drones, robotics and IoT sensors work together to increase output and drastically decrease price. Figure 6.2 shows applications of data science and cloud repository.

Fig. 6.2
An infographic of the application of data science in analytics includes early disease detection, prediction of climate change, fertilizer recommendation, autonomous irrigation systems, and digital soil and crop mapping.

Applications of data science in data analytics and cloud repository

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Recent Development Scenarios in 5G-Based Agriculture

Relevant Literature based on recent development scenarios in 5G-based agriculture concerning UAVs, predictive maintenance, AR and VR, real-time monitoring and agribots are summarized as follows (Table 6.1).

Table 6.1 Recent development scenarios in 5G-based agriculture
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Conclusion and Future Work

The 4G network although allows faster data transmission rates and adequate coverage, it is unable to transmit the massive amount of data between the number of devices. 5G comes into picture to meet the requirement of precision agriculture for improved output with a lesser amount of effort. In the forthcoming days, the 5G networks will be implemented in all industries; so, internet price will be much reduced and connectivity is going to be boosted. The utilization of 5G will drastically lower the implementation costs, which will be a godsend to farmers. Farmers will be well equipped for smart farming, with the capacity to use their mobile phones to forecast and prevent crop disease. By expanding their physical infrastructure, mobile carriers will make substantial contributions to precision agriculture. Data from the field will be collected by sensors and saved in the cloud. Sensors having a prolonged battery life will grow smaller and less expensive and networks will be more efficient, become smarter as well as secured. Although 5G has several applications and benefits in the agricultural industry, it will fundamentally alter the structure of jobs. There’s a good chance that the number of agricultural jobs will decrease. Specific power supervision approaches, like sleep modes, have to be implemented to map the 5G network’s no-load traffic allocation and maximize the use of harvested energy. To accomplish the ideal active periods of the 5G base stations while fulfilling the quality of service rendered, the active times of IoT devices should be efficiently coordinated.