5.1 Role of IoT and Cloud in Smart Agriculture

The Internet of Things (IoT) is a game-changing innovation that facilitates future of communication and information technology. Agriculture is the lifeblood of the majority of people on the planet. As a result, smart IT techniques are required to integrate traditional agricultural methods. Modern technology may help manage costs, maintenance, and performance monitoring. In today’s agriculture, satellite and aerial photography are critical. Smart Agriculture is a rising, cost-effective approach for agricultural and food production that is both efficient and reliable. It’s a technique for incorporating connected gadgets and cutting-edge innovation into agriculture. The IoT has brought great advantages to agriculture, including efficient water usage, input augmentation, and many more. The immense gains that have lately changed farming were what made all the difference. IoT-based Smart Farming improves the overall agricultural system by monitoring the field in real-time.

Because of sensors and connectedness, the IoT in Farming has not only reduced farmers’ time but also reduced resource waste such as electricity and water. It keeps track of a number of factors, including moisture, temperature, and soil, and displays them in a crystal-clear real-time display. In order to meet increased demand and decrease production losses, IoT applications in agriculture are directed at conventional agricultural tasks. In agriculture, drones, UAVs, sensor systems, and computer imaging are used in conjunction with ever-improving machine learning and data mining techniques to observe crops, measure and map fields, and transmit data to farmers for cost-effective farm management. In aggrotech, the IoT is a system that combines sensitive physical equipment with analytical software. The majority of the time, an analytical dashboard is a piece of software that processes data collected by equipment. As a result, a solid technical grasp of robotics and computer-based intelligence is required for operating, maintaining, and comprehending the thoughts of these priceless machines. Because IoTs need actual equipment, each farm will require its own collection of sensors and bots to capture data specific to that farm. As a result, each farm will have its own dashboard to see the data. It is not feasible to connect and scale IoT for several fields in a single platform, unlike SaaS aggrotech like CropIn, which allows you to integrate and manage global operations via a single platform.

Sensors have been downsized as a result of recent advances in developing technologies, and attempts to utilize them in a variety of disciplines have been effective. Furthermore, the adoption of IoT and Cloud Computing in any area is resulting in the notion of “Smart,” which includes Smart Health Systems [1], Pervasive Computation, Smart Mobility, Embedded Systems, Security Systems, and Smart meters [2], among others. Agriculture is one of the fields of research where this acceptance has occurred, culminating in Smart Agriculture. Agriculture is a critical source of revenue and lifestyle for the world’s most populated countries, including India, China, and many others. Incorporating IoT and Cloud Computing into the agricultural industry would result in improved crop production by regulating costs, tracking progress, and maintaining equipment, all of which would assist farmers and the country as a whole. The comparative study of latest papers related to Smart Agriculture and IoT is shown above in Table 5.1.

The growing need for food, in terms of quantity and quality, has hastened the need for agricultural industrialization and aggressive techniques of production. A rising IoT market is proposing various unique ideas at the vanguard of the new farming era. Connecting with IoT allows research institutions and scientific associations to expand their reach and speed, bringing technologies and goods to a variety of farm sectors. The IoT is a developing framework that aims to synchronize various smart devices in order to modernize multiple domains. Several IoT-based frameworks have been proposed to record and handle agricultural areas with optimum human interaction in an automated way. Farmers [10] may use IoT apps to stay up to date on the recent developments and advances in their area. Furthermore, the availability of cloud-based smart apps and models aids farmers in maintaining control over their crops. Such technologies, for instance, have the capacity to gather data, analyses it, and predict the optimal response in various scenarios in order to tackle the anticipated issue. Problems like this arise as a consequence of unfavorable weather and a variety of crop diseases.

The IoT is transforming agriculture by giving farmers with a varied collection of tools to handle a variety of difficulties they experience on the farm. IoT-enabled technology allows farmers to communicate to their farm from practically anywhere and at any time. Sensors and actuators monitor the agricultural procedure, in which, wireless sensor networks are utilized to regulate the farmland. To access the farm remotely and gather information in the form of films and photographs, wireless sensors and cameras were utilized. Farmers can also utilize IoT to monitor the present state of their agricultural land from anywhere in the world using a smart phone. IoT-enabled solutions have the ability to reduce crop production costs while also increasing agricultural production.

5.2 Applications of IoT and Cloud in Smart Agriculture

IoT Modern electronic agriculture is made possible by smart technology. To handle today’s issues, innovation has become a requirement, and various industries are automating their processes using the latest advancements. Smart agriculture [11], which is built on IoT technology, is designed to help producers and farmers minimize waste and increase output by regulating fertilizer use to increase process efficiency. Farmers can better regulate their animals, develop crops, decrease expenses, and conserve resources using IoT-based Smart Agriculture. Farmers have benefited from the use of IoT in a variety of ways, including monitoring water quantities in tanks. This is all done in real time, which improves the effectiveness of the entire irrigation operation. The monitoring of seed growth is another thing which has been made feasible by the introduction of IoT technology. Producers can now monitor resource use and the time it takes for a seed to completely mature into a plant.

The adoption of IoT in farming was akin to the Green Revolution’s second wave. Farmers have reaped two main advantages from the IoT. With the support of reliable data collected via IoT, they can now do the same number of jobs in less time while simultaneously increasing agricultural yields. Sensors monitor every aspect of crop production, including moisture in the soil, temperature, sunlight, climate, and irrigation management automation. This technique enables farmers to keep an eye on their fields from anywhere. When compared to traditional farming, IoT-based farming is significantly more efficient. Smart farming based on IoT not only aids in the modernization of traditional farming techniques, but also targets alternative agricultural methods such as sustainable agriculture, family farming, and boosts extremely transparent farming. Smart farming based on the IoT is also good for the environment. It may assist farmers in making better use of water and optimizing inputs and treatments. Now, we will look (Figure 5.1) at the applications of IoT and cloud in the smart agriculture that are transforming the agricultural industry.

• IoT powered drones: In recent years, technology has advanced dramatically and at a faster pace. Agricultural drones are an excellent illustration of this trend. Drones are being used in agriculture to enhance a variety of agricultural processes. Drones are used in agriculture for crop health evaluations, cultivation practices, pest management, drainage, sowing, and field analysis, both on the ground and in the air. These drones acquire spectral bands, thermal, and visual pictures during their flight. Crop health surveillance, integrated GIS mapping, improved efficiency, ease of use, and enhanced agricultural yields are just a few of the benefits of drones. Numerous benefits have been predicted for real-time applications as a result of recent breakthroughs in quantum drones, the Internet of Quantum Drones [12], and Drone-to-Satellite connection. We can give the agriculture industry a high-tech makeover if we integrate surveillance drones with effective planning and strategy based on real-time data collecting.

  

• Observing Livestock: Large farm operators use wireless IoT apps to keep track of their cattle’s whereabouts, health, and well-being. This knowledge [13] aids them in identifying ill animals and separating them from the flock, as well as caring for them and preventing the sickness from spreading to other livestock. It may also help owners save money on labor since IoT-based sensors can assist them find their animals.
• Intelligent Greenhouses: Greenhouse farming aims to increase vegetable, agricultural, and fruit yields, among other things. In greenhouses, climate effects are managed via human interaction or a proportional control system. On the other side, manual participation leads in reduced productivity, power dissipation, and labor expenses. Therefore, the concept of greenhouses has been made obsolete. Consequently, smart gardens are the better alternative. A smart greenhouse might be developed with the help of IoT. Autonomous greenhouses, on the other hand, monitor and control the atmosphere without requiring human intervention.
• Irrigation Monitoring: Computer imaging mostly entails deploying sensor cameras strategically positioned across the farm to create pictures that are then processed digitally. Irrigation throughout time assists in the mapping of irrigated fields. This allows determining whether to produce or not harvest during the pre-harvest season.
• Weather Monitoring: Crop productivity is influenced by the weather. Varied crops need different climatic conditions to develop, and even a rudimentary understanding of climate has a significant impact on crop amount and quality. Farmers may use IoT technologies to get real-time weather updates. Sensors installed in agricultural fields gather information from the environment, which farmers use to select a crop that can thrive in certain climatic circumstances.
• Accurate Farming: Precision farming, often known as smart farming, refers to any method of raising animals and cultivating crops that renders the entire process more precise and regulated. Sensors, robots, automation trucks, control mechanisms, automated equipment, variable rate innovation, and other advancements are all important components of this farming approach.
• Remote Sensing: Sensors installed along fields, such as meteorological stations, are used in IoT-based remote sensing to collect data, which is then sent on to analysis instruments for study. Farmers may keep an eye on their crops using analytical interfaces, and take action based on the information gleaned.

5.3 Security Challenges in Smart Agriculture

The IoT is a collection of physical items that can recognize themselves to other gadgets and utilize integrated technology to communicate with intrinsic or extrinsic states. Many computing devices with monitoring and communication capabilities are now linked due to advances in technology. Such devices [14] collect information from the environment, process it, and then either retain or transfer the information to another device with comparable characteristics. A few examples [15] of IoT applications are smart homes, intelligent buildings, smart grids, and smart cars. For remote access, collection, distribution, and processing, these applications need distributed information delivery architectures. As a consequence, communication among smart things opens up new possibilities for applications aimed at improving human health. Enormous communication inside these cyber-physical systems, on the other hand, raises a slew of security issues. Such security [16] flaws have the potential to disrupt whole applications/ systems, perhaps resulting in death. As a result, modern IoT applications must have high levels of trust and security. To that aim, it’s critical to comprehend the major security issues that smart IoT applications face, such as those in the e-health, agricultural, and energy industries. As a result, in order to improve the security of smart IoT applications, this article describes and addresses the key security issues and needs.

Attacks on the IoT system may be interpreted or characterized from a variety of perspectives, depending on whether they are aggressive or passive. These may also be used to determine if the assault is coming from the inside of the network or from outside. In any instance, information security and anonymity must be protected. In IoT case studies, the customer has access to the data and the authorized machine, information confidentiality is a critical concern. It involves addressing two key features: first, a means for validating and verifying identities, and second, an admission limitation and penalty process. The verification of a legal IoT device is the confirmation of the identification of the IoT based networks for internet or fog-based services. To utilize the cloud services safely, IoT apps must verify their identity. User confidentiality is another difficult issue with real-time apps. With IoT applications where devices are interconnected, privacy is another major challenge. The IoT related common cyberattacks in smart agriculture are given below in Figure 5.2.

• Routing Protocols attacks: Such type of attack targets the various routing protocols used in the IoT communication and is responsible for packet loss, downgrading network bandwidth, poor throughput, and data loss.
• Internal/External attacks: Internal attacks are those attacks that are done by the insider of the organization or in which some internal person of the organization is involved. The extremal attacks are those in which some external factor is involved like attack from outside the organization e.g. phishing, etc.

  

• Malware based attacks: In this type of attacks, some mal-ware is involved like rootkit, Trojan, virus, worm, etc. This attack may lead to the data theft, unnecessary utilization of resources, privacy breach, and data tampering.
• Denial of Service (DoS) attacks: This attack comes into picture when some non-legitimate user(s) is trying to restrict the legitimate user(s) from using the services. This attack may also lead to network flooding, unavailability of the resources and system crash.
• RFID or Sensors Spoofing Attacks: In this attack, RFID/ sensors are faked out to fool the target. This type attack may lead to modification of data and manipulation of it.
• Man in the Middle (MITM) attacks: MITM attacks are due to network eavesdropping, when an intruder wiretaps the network to sniff it. This attack may leads to breach of confi-dentiality and privacy, and data leakage.

Agricultural knowledge and digitization are addressed by smart agriculture. With the advancement of agriculture spurred on by current digital technology, however, data security risks must be addressed. Three distinct smart sustainable agriculture modes are discussed in this research [17]. Sustainable farming is still in its infancy, with few security mechanisms. Future solutions will rely on data accessibility and accuracy to aid farmers, and security will be critical to constructing reliable and productive systems. Because smart agriculture carries a wide variety of resources and huge amount of data, security must handle challenges such as interoperability, less number of resources, and enormous data. The aim of this study [18] is to assess the existing level of smart agricultural security, especially in open-field farming, by explaining its design, outlining security diffi-culties, and providing important obstacles and future perspectives. In the agricultural industry, new information technologies and applications will be increasingly employed to maintain and enhance operations, efficiency, and productivity. The widespread use of information, meanwhile, brings with it significant security dangers and weaknesses, and the industry is now being attacked like never before. Using an analytical technique, some comments on the security difficulties that Smart Farming technologies confront are presented in this study [19].

5.4 Open Research Challenges for IoT and Cloud in Smart Agriculture

Smart Agriculture is a promising field that is evolving day by day due to the support of advanced technologies like IoT, Cloud Computing, Artificial Intelligence, Cybersecurity, Blockchain etc. Due to its wide nature, it provides a vast array of research scope and opportunities. This section highlights the open research challenges for IoT and cloud computing in Smart Agriculture. IoT is a developing paradigm that aims to link various smart hardware elements for various domain upgrading. Several IoT-based definitions have been developed to autonomously manage and monitor agricultural areas with minimum human interaction. The primary components, new technology, security problems, obstacles, and emerging developments in the agricultural area are all discussed in depth in this article [20]. The open research challenges for IoT and cloud in smart agriculture is shown below in Figure 5.3.

• Compliance: The legislative and legal mechanisms regulating the administration and custody of agricultural data between farm employees and data businesses must be sorted out. In accordance with the service offering, technical problems, profitability, information security, and security, regulations differ per nation. Various regulations in different parts of the globe might influence how IoT is used in certain applications like surveillance and food production.
• Business aspects: Because the agriculture industry has a low market share, it is necessary to balance the deployment of IoT-enabling technology with the anticipated advantages. Installation and operational expenses are two types of costs connected with IoT adoption in agriculture. The installation fee includes the cost of IoT devices necessary to create a smart agricultural setting. A lack of information of IoT and its uses, particularly among rural farmers regions, is a major impediment to IoT adoption in agribusiness.
• Expansion and reliability: Huge count of IoT devices and detectors are used in smart agriculture, requiring the employment of a smart IoT management system to identify and regulate each node. IoT devices are designed to be put in the open air. This exposing the devices to harsh external conditions, which might lead to sensor degradation and communication issues over time.
• Resource optimization: To increase profitability, farmers need a resource optimization procedure to determine the ideal count of access points, IoT devices, conveyed data, and cloud storage. This is complicated by the fact that different farms have different dimensions and need different kinds of sensors to identify agricultural factors for specific crops or animals.
• Network challenges: The connectivity between numerous sensor units in smart agriculture poses a challenging task. Sensors [21] do enormous calculations that need a lot of energy, yet sensor batteries are limited. As a consequence, efficient energy storage is required by networks. These issues don’t simply exist at the device implementation level; they also emerge at the network level.
• Security and privacy issues: Physical tampering [22], such as burglary or assaults by rats and cattle, as well as differences in physical location or link, are all possibilities in the smart agricultural area. At various tiers of IoT, the authors [23] tackled various security breach situations such as security breaches, SQL Injection attacks, and so on. The perception layer is primarily focused on physical devices such as sensors and actuators. Accidental or intentional human action, viruses, or hackers may lead to physical equipment to fail.

Information became fragmented since the number of research and initiatives regarding IoT-based sustainable farming grew rapidly, and he related communications systems were not previously studied and addressed in prior reviews. To achieve the wonderful ahead expansion in smart agriculture, more emerging communications systems should be utilized in agricultural production, according to the report [24].

5.5 Conclusion

IoT allows for the collection of massive amounts of data through sensors, allowing for improved management of internal operations and, as a consequence, fewer production hazards. The Internet of Things allows for effective monitoring of the agricultural environment. By providing remote monitoring, the Internet of Things allows farmers to watch their farms from numerous places. Decisions may be taken instantly and from any location. In this chapter, the applications of smart agriculture using Cloud and IoT are discussed. Moreover, the cyberattacks on IoT applications in the field of smart agriculture is also highlighted in this chapter. Smart agriculture relies largely on the IoT, which reduces the need for local farmers to do physical work and so boosts productivity in every manner possible. The book chapter highlighted the role of IoT and cloud in smart agriculture. The chapter also enlightened the readers about the research scope of IoT and cloud in Smart Agriculture. The chapter is also helpful for the IoT enthusiasts, cloud security experts, Ph.D. scholars, researchers and students.

References

1. 1. Singh, K., Kaushik, K., Ahatsham, Shahare, V., Role and impact of wearables in IoT healthcare. Adv. Intell. Syst. Comput., 1090, 735–742, 2020.
2. 2. Jain, S., Kaushik, K., Sharma, D.K., Krishnamurthi, R., Kumar, A., Sustainable infrastructure theories and models, in: Digit. Cities Roadmap, pp. 97–126, Apr. 2021.
3. 3. Mekala, M.S. and Viswanathan, P., A survey: Smart agriculture IoT with cloud computing. 2017 Int. Conf. Microelectron. Devices, Circuits Syst. ICMDCS 2017, Dec. 2017, vol. 2017-January, pp. 1–7.
4. 4. Namani, S. and Gonen, B., Smart agriculture based on IoT and cloud computing. Proc. - 3rd Int. Conf. Inf. Comput. Technol. ICICT 2020, Mar. 2020, pp. 553–556.
5. 5. Lakhwani, K. et al., Development of IoT for smart agriculture a review. Adv. Intell. Syst. Comput., 841, 425–432, 2019.
6. 6. Mekala, M.S. and Viswanathan, P., CLAY-MIST: IoT-cloud enabled CMM index for smart agriculture monitoring system. Measurement, 134, 236–244, Feb. 2019.
7. 7. Ramachandran, V., Ramalakshmi, R., Srinivasan, S., An automated irrigation system for smart agriculture using the Internet of Things. 2018 15th Int. Conf. Control. Autom. Robot. Vision, ICARCV 2018, Dec. 2018, pp. 210–215.
8. 8. Kalyani, Y. and Collier, R., A systematic survey on the role of cloud, fog, and edge computing combination in smart agriculture. Sensors, 21, 17, 59225922, Sep. 2021.
9. 9. Suma, V., Internet of Things (IoT) based smart agriculture in India: An overview. J.ISMAC, 03, 01, 1–15, 2021, https://doi.org/10.36548/jismac.2021.1.001
10. 10. Tawalbeh, M., Quwaider, M., Tawalbeh, L.A., IoT cloud enabeled model for safe and smart agriculture environment. 2021 12th Int. Conf. Inf. Commun. Syst. ICICS 2021, pp. 279–284, May 2021.
11. 11. Gaur, C., IoT in smart agriculture solutions and applications | Use case, Oct. 20, 2021, https://www.xenonstack.com/use‐cases/iot‐smart‐farming (accessed Dec. 01, 2021).
12. 12. Kumar, A., Bhatia, S., Kaushik, K., Gandhi, S. M., Devi, S. G., Diego, Di. A., & Mashat, A., Survey of promising technologies for quantum drones and networks. IEEE Access, 9, 125868–125911, 2021, https://doi.org/10.1109/ACCESS.2021.3109816
13. 13. Pathak, R., 7 Applications of IoT in agriculture | Analytics steps, Dec. 23, 2020, https://www.analyticssteps.com/blogs/5‐applications‐iot‐agriculture (accessed Dec. 01, 2021).
14. 14. Kaushik, K. and Singh, K., Security and trust in IoT communications: Role and impact, in: Advances in Intelligent Systems and Computing, vol. 989, pp. 791–798, 2020.
15. 15. Tariq, N., Khan, F.A., Asim, M., Security challenges and requirements for smart Internet of Things applications: A comprehensive analysis. Proc. Comput. Sci., 191, 425–430, Jan. 2021.
16. 16. Kaushik, K. and Dahiya, S., Security and privacy in IoT based e-business and retail. Proc. 2018 Int. Conf. Syst. Model. Adv. Res. Trends, SMART 2018, pp. 78–81, Nov. 2018
17. 17. Yang, X. et al., A survey on smart agriculture: Development modes, technologies, and security and privacy challenges. IEEE/CAA J. Autom. Sin., 8, 2, 273–302, Feb. 2021.
18. 18. Rettore de Araujo Zanella, A., da Silva, E., Pessoa Albini, L.C., Security challenges to smart agriculture: Current state, key issues, and future directions. Array, 8, 100048, Dec. 2020.
19. 19. Barreto, L. and Amaral, A., Smart farming: Cyber security challenges. 9th Int. Conf. Intell. Syst. 2018 Theory, Res. Innov. Appl. IS 2018 - Proc., Jul. 2018, pp. 870–876.
20. 20. Sinha, B.B. and Dhanalakshmi, R., Recent advancements and challenges of Internet of Things in smart agriculture: A survey. Future Gener. Comput. Syst., 126, 169–184, Jan. 2022.
21. 21. Saha, H.N., Roy, R., Chakraborty, M., Sarkar, C., IoT-Enabled agricultural system application, challenges and security issues, in: Agric. Informatics, pp. 223–247, Mar. 2021.
22. 22. Haseeb, K., Din, I.U., Almogren, A., Islam, N., An energy efficient and secure IoT-based WSN framework: An application to smart agriculture. Sensors, 20, 7, 20812081, Apr. 2020.
23. 23. Demestichas, K., Peppes, N., Alexakis, T., Survey on security threats in agricultural IoT and smart farming. Sensors, 20, 22, 64586458, Nov. 2020.
24. 24. Tao, W., Zhao, L., Wang, G., Liang, R., Review of the internet of things communication technologies in smart agriculture and challenges. Comput. Electron. Agric., 189, 106352, Oct. 2021.