A Tutorial on Agricultural IoT: Fundamental Concepts, Architectures, Routing, and Optimization

The emergence of Internet of Things (IoT) technology has significantly altered various aspects of everyday life, instilling intelligence into nearly everything. In the expansive realm of IoT applications, the incorporation of IoT into smart agriculture has captured the attention of numerous researchers, utilizing both Machine Learning (ML) and IoT technologies for groundbreaking investigations. The application of IoT-driven, data-centric techniques in farm management has the potential to enhance agricultural outcomes by strategically planning input costs, reducing losses, and optimizing resource utilization. The substantial volume of data generated by IoT, exhibiting diverse features based on location and time, requires thorough analysis and processing to enhance agricultural efficiency through intelligent farm management. As more and more data is gathered, the powerful processing powers of machine learning open up new avenues for data-intensive study. Applications' intelligence and usefulness may be further improved by leveraging machine learning techniques. This paper looks closely at previous attempts at smart farming and agriculture, with particular attention on IoT and ML. Furthermore, it introduces innovative concepts proposing the seamless integration of ML and IoT in such applications. [1] V.

Internet of Things technology plays a significant role in agriculture industry. The recent statistics shows that the world population is on the point of reach over 9 billion in the year 2050. The agriculture industry needs to adopt the smart technology to feed this large population. The agriculture Industry depends on innovative ideas to manage growing demand for food. The agriculture operations need smart solutions from IoT by introducing satellite connectivity and expending cellular networks. The entire Agriculture system is improved using IoT based Smart Farming monitoring the field in real-time. Sensors and interconnectivity helps the Internet of Things in Agriculture has not only saved the time of the farmers but has also reduced the extravagant use of resources such as Water and Electricity.

The agricultural industry must rise to meet demand, regardless of environmental issues such as unfavourable weather and climate change, in view of an increasing population, currently expected to hit 9.6 billion by 2050. Agricultural industries would need to use emerging technology to gain an advantage in order to meet the needs of the increasing population. Increased operating productivity, lower costs, reduced waste and improved quality of the yield of new agriculture applications for IoT and smart agriculture would help. In these lines, make use of wireless sensor networks in agriculture as well as its difficulties in implementation in agri-environment and use of IoT and its use in agri-sector as well as biofuels through smart agriculture were revealed.

Agriculture is one of the major sources of economy in the country. Precision Agriculture is already in implementation in other countries but there is a need to implement, improve and evolve IoT(Internet of Things) and cloud computing technologies for better production of the crop. There is a steady increase in demand with population growth. Modernization in agriculture reduces dependency on individual human labor and land. The technology allows operational devising and accelerates verdict making on Farms. IoT allows us to accumulate surrounding data, stock it, concoct it and disseminate the information. The adoption of cloud computing has undergone a huge rise in need and would continue to grow in the coming future with improved cloud hosting and processing dexterities. AI(Artificial Intelligence) and IoT is a great lead as a solution to increased productivity. The data through IoT devices is made available publically for research purposes as data sets and is processed and examined for further prediction related to the crop being produced. The Traditional Technique of farming does not involve any process such as seed selection, soil analysis, weather analysis, vegetation analysis, Nutrient analysis if all these factors are taken in care, this all would bring a drastic change in the society. The System also has a block-chain based shipping system to ensure proper distribution without any wastage. Though the pen-paper tradition is hard to be replaced but minimizes a lot of work, moreover the analysis of manual work required can also be analyzed. A more intricate approach to IoT products in agriculture can be represented by the so-called farm productivity management systems. They usually include several agriculture IoT devices and sensors, installed on the premises as well as a powerful dashboard with analytical capabilities and inbuilt accounting/reporting features. In addition to the listed IoT agriculture use cases, some prominent opportunities include vehicle tracking (or even automation), storage management, logistics, etc.

An adaptive medium access control (MAC) retransmission limit selection scheme is proposed to improve the performance of IEEE 802.11p standard MAC protocol for video streaming applications over vehicular ad-hoc networks (VANETs). A multi-objective optimization framework, which jointly minimizes the probability of playback freezes and start-up delay of the streamed video at the destination vehicle by tuning the MAC retransmission limit with respect to channel statistics as well as packet transmission rate, is applied at road side unit (RSU). Periodic channel state estimation is performed at the RSU using the information derived from the received signal strength (RSS) and Doppler shift effect. Estimates of access probability between the RSU and the destination vehicle is incorporated in the design of the adaptive MAC scheme. The adaptation parameters are embedded in the user datagram protocol (UDP) packet header. Two-hop transmission is applied in zones in which the destination vehicle is not within the transmission range of any RSU. For multi-hop scenario, we discuss two-hop joint MAC retransmission adaptation and path selection. Compared with the non-adaptive IEEE 802.11p standard MAC, numerical results show that the proposed adaptive MAC protocol exhibits significantly fewer playback freezes while introduces only a slight increase in start-up delay.

Priority based [formula omitted] dominance: A new measure in multiobjective optimization

This research aims to analyse the applications of IoT in agriculture and to compare the most widely used IoT platforms. The problem of determining the most appropriate IoT system depends on many factors, often expressed by incomplete and uncertain estimates. In order to find a feasible decision, this study develops a multi-criteria framework for IoT solution selection in a fuzzy environment. In the proposed framework, a new modification of the Multi-Attribute Border approximation Area Comparison (MABAC) method with a specific distance measure via intuitionistic fuzzy values has been presented as a decision analysis method. The new technique is more precise than existing crisp and fuzzy analogues, as it includes the three components of intuitionistic numbers (degree of membership, degree of non-membership and hesitancy degree) and the relationships between them. The effectiveness of the new decision-making framework has been verified through an illustrative example of ranking IoT platforms.

Building IoT applications of added-value from a set of available devices with minimal human intervention is one of the main challenges facing the IoT. This is a difficult task that requires models for specifying objects, in addition to user-friendly and reliable composition techniques which in turn prevent the design of erroneous applications. In this work, we tackle this problem by first describing IoT applications using abstract models obtained from existing models of concrete devices. Then, we propose automated techniques for building compositions of devices using a repository of available devices, and an abstract goal of what the user expects from such compositions. Since the number of possible solutions can be quite high, we use both filtering and ranking techniques to provide the most pertinent solutions to users. The provided solutions satisfy the given goal and may be analysed with respect to properties such as deadlock-freeness or unmatched send messages. Finally, the application can be deployed using existing execution engines.

This paper addresses the medium access control (MAC) and physical (PHY) cross-layer design of a time-division multiple access protocol (TDMA) where users with good channels are allowed to relay the packets of other users with less favorable conditions. All signals are combined at the central node using signal processing tools in order to achieve diversity. The work is focused on an asymmetrical scenario where users experience different channel and queuing states. Two performance metrics are used: packet throughput and access delay. To facilitate the analysis, a packet reception model which represents more efficiently the cooperative PHY layer is also proposed. A multi-objective optimization is used to derive the boundaries of the throughput region, i.e., the set of all achievable user throughput values. Sketches of the two-user case show that the region is always convex and larger than the region of its non-cooperative counterpart. The results also show that cooperation is useful when some users with good channels experience low/medium traffic loads and thus can help other users with bad channels and higher traffic loads. Evaluation of access delay is also obtained by using the expressions of a modified TDMA system.

JavaScript code running in the Node.js runtime is a major platform for developers building cloud, mobile, or IoT applications. A fundamental concept in Node.js programming is the use of asynchronous callbacks and event loops to provide highly responsive applications. While conceptually simple, this programming model contains numerous subtleties and behaviors that are defined implicitly by the current Node.js implementation. This paper presents the first comprehensive formalization of the Node.js asynchronous execution model and defines a high-level notion of async-contexts to formalize fundamental relationships between asynchronous executions in an application. These formalizations provide a foundation for the construction of static or dynamic program analysis tools, support the exploration of alternative Node.js event loop implementations, and provide a high-level conceptual framework for reasoning about relationships between the execution of asynchronous callbacks in a Node.js application.

Objective: Grounded in the Unified Theory of Acceptance and Use of Technology (UTAUT), this study aims to examine patients’ behavioral intention (BI) toward accepting electroacupuncture analgesia and identify key determinants that influence its adoption. Methods: We conducted a multicenter cross-sectional study with questionnaire-based data collection and analyzed associations using structural equation modeling (SEM). Reporting followed the STROBE guidelines. Results: A total of 325 participants were included in the analysis. Performance expectancy (PE) ( β = 0.272, p < 0.001), effort expectancy (EE) ( β = 0.610, p < 0.001), and facilitating conditions (FC) ( β = 0.586, p < 0.001) exhibited significant positive effects on BI. Social influence did not exert a significant effect ( β = 0.217, p = 0.090). FC had a significant negative effect on use behavior (UB) ( β = −0.617, p < 0.001), forming a competitive mediation model with its positive indirect effect via BI. Significant differences in BI were observed across participants of different age groups, social backgrounds, educational levels, occupations, and income levels ( p < 0.05). The model exhibited a good fit, supporting the applicability of the theoretical framework. Conclusion: EE, PE, and FC are key factors influencing patients’ acceptance of electroacupuncture analgesia. FC exhibited a competitive mediation effect on UB, highlighting the necessity of optimizing convenience conditions to meet the higher expectations of experienced users. Future initiatives should focus on developing tailored strategies for diverse demographic groups to enhance the clinical adoption and therapeutic effectiveness of electroacupuncture technology.

Reliable and cost-efficient session provisioning in CRNs using spectrum sensing as a service

The pervasiveness of ubiquitously connected smart devices are the main factors in shaping the computing. With the advent of Internet of things (IoTs), massive amount of data is being generated from different sources. The centralized architecture of cloud has become inefficient for the services provision to IoT enabled applications. For better support and services, fog layer is introduced in order to manage the IoT applications demands like latency, responsiveness, deadlines, resource availability and access time etc. of the fog nodes. However, there are some issues related to resource management and fog nodes allocation to the requesting application based on user expectations in the fog layer that need to be addressed. In this paper, we have proposed a Framework, based on Model Driven Software Engineering (MDSE) that practices Machine Learning algorithms and places fog enabled IoT applications at a most suitable fog node. MDSE is meant to develop software by exploiting the problem at domain model level. It is the abstract representation of knowledge that enhances productivity by maximization of compatibility between the systems. The proposed framework is a meta-model that prioritizes the placement requests of applications based on their required expectations and calculates the abilities of the fog nodes for different application placement requests. Rules based machine learning methods are used to create rules based on user’s requirements metrics and then results are optimized to get requesting device placement in the fog layer. At the end, a case study is conducted that uses fuzzy logic for application mapping and shows how the actual application placement will be done by the framework. The proposed meta-model reduces complexity and provides flexibility to make further enhancements according to the user’s requirement to use any of the Machine Learning approaches.

Recent advances in self-interference cancellation techniques enable in-band full-duplex (FD) transmission in which a wireless node can simultaneously transmit and receive in the same frequency band. However, to fully exploit the benefits of FD technology in a wireless network, in addition to the physical (PHY) layer issues, medium access control (MAC) layer issues such as inter-node collisions, fairness between halfduplex (HD) and FD users, opportunistic selection of different modes of FD transmission, and synchronization issues need to be resolved. To this end, this article first discusses the fundamental concepts, potential benefits, and primary network topologies of FD transmission. We then highlight immediate challenges (both in the PHY and MAC layers) that need to be addressed in designing FD wireless systems. A qualitative comparison among the existing full-duplex MAC (FD-MAC) protocols is then provided. Finally, the primary requirements and research issues for the design of FD-MAC protocols are discussed, and implications of FD technology in cellular wireless networks are highlighted.

Pendulum clocks were the prevalent time keeping standard for centuries to regulate commerce and public activities. These mechanical movements were the most accurate timekeepers globally until replaced by electric clocks. Although mainly used for decorative purposes today, the pendulum clock's working principles and mechanical behavior can serve to demonstrate fundamental science and engineering concepts. The tradeoff between a clock's quality factor, pendulum properties, and period can best be explored with multiple objective optimization and tradespace analysis methods. In this project, a Multi-Objective Genetic Algorithm (MOGA-II) and a Multi-Objective Simulated Annealing (MOSA) optimization approaches are applied to evaluate a Graham escapement street clock for pendulum mass and time accuracy with a range of the period. These clock designs vary the pendulum length, pendulum bob radius, and bob thickness. Horological concepts are used to calculate the overall performance and general utility. The numerical results show a 0.7% increase in the quality factor, and a 0.56% reduction in the mass, while maintaining the designed period by modifying the clock parameters. More importantly, these changes can provide material cost savings in a mass production scenario. Overall, the study highlights the tradeoff designer engineers have considered for decades which can now be visualized using computer tools for greater insight.