Efficient Data Management in Agricultural IoT: Compression, Security, and MQTT Protocol Analysis.

ABSTRACTIn recent years, the emerging development of Internet of things (IoT) has created new opportunities for IoT service provider, device manufacturer and customer (end user). In agriculture, employing IoT can help reducing manpower as well as standardizing agricultural processes, thus increasing the benefit for customer who does agricultural business. Beside the opportunities, there are also issues while doing maintenance for an agricultural IoT system. One of them is how to automate the process to detect faults of IoT devices in a large deployment area. While previous studies focus on investigating algorithms as well as theoretical model to detect faults for specific IoT devices, automatically expanding of IoT management process for detecting faults of sensor/actuator has not been investigated yet. To achieve this, we should be able to deal with the relationship between IoT device manufacturer, service provider and customer. In this study, we conceptualize the knowledge of IoT devices, management process and fault detection requirement. To realize this model, we introduce a runtime system to expand the IoT management process for detecting sensor/actuator faults which is able to provide the above features. We do several experiments to show the effectiveness and usefulness of the proposed solution.

With the rapid development of the internet of things (IoT), traditional industries are setting off a massive wave of digitization. In the era of the Internet of Everything, millions of devices and links in IoT pose more significant challenges to data management. Most existing solutions employ centralized systems to control IoT devices, which brings about the privacy and security issues in IoT data management. Recently, blockchain has attracted much attention in the field of IoT due to its decentralization, traceability, and non-tamperability. However, it is non-trivial to apply the current blockchain techniques to IoT due to the lack of scalability and high resource costs. Different blockchain platforms have their particular advantages in the scenario of IoT data management. In this paper, we propose a cross-chain framework to integrate multiple blockchains for efficient and secure IoT data management. Our solution builds an interactive decentralized access model which employs a consortium blockchain as the control station. Other blockchain platforms customized for specific IoT scenarios run as the backbone of all IoT devices. It is equivalent to opening the off-chain channels on the consortium blockchain. Our model merges transactions in these channels for confirmation based on the notary mechanism. Finally, we implement a prototype of the proposed model based on hyperledge Fabric and IOTA Tangle. We evaluate the performance of our method through extensive experiments. The results demonstrate the effectiveness and efficiency of our framework.

The integration of big data and the Internet of Things (IoT) is revolutionizing agriculture by providing new solutions for precision farming, resource optimization, and sustainable practices. By combining real-time data from IoT devices, such as sensors, drones, and satellites, with the vast analytical power of big data, farmers can make more informed decisions to improve crop yields, monitor soil health, manage water usage, and optimize fertilizer application. This article explores the role of big data and IoT in smart agriculture, focusing on how these technologies can improve operational efficiency, increase productivity, and promote sustainable practices in agriculture. It also discusses the challenges and future directions for integrating big data and IoT in the agriculture sector.

The Internet of Things (IoT), which seamlessly interconnects heterogeneous devices with diverse functionalities, is an attractive choice for the large-scale petrochemical industry to develop an integrated system. With the industrial revolution, efforts have mainly been focused on factory automation, transportation security, and surveillance. The IoT plays a major role in factories with its new methods of data management and data collection. However, the IoT is still at an early stage in large-scale petrochemical plants due to the multiple coexisting heterogeneous networks in harsh and complex large-scale industrial networks. This paper presents a comprehensive survey on the IoT in large-scale petrochemical plants as well as recent activities in communication standards for the IoT in industries. This paper addresses the key enabling middleware approaches, e.g., an industrial intelligent sensing ecosystem (IISE), which allows rapid deployment and integration of heterogeneous wireless sensor networks with advancements in crowdsensing based services. In addition, this survey highlights the research issues of data management in the IoT for large-scale petrochemical plants.

This study investigates hybrid energy harvesting(EH) as a sustainable and efficient power solution for Internet of Things (IoT) devices. Traditional battery-powered and single-source energy systems have limitations, such as limited lifetime and unreliable power availability. To address these issues, a hybrid energy harvesting system is proposed that combines photovoltaic energy (solar), radio frequency energy(RF) , and vibration energy sources. These sources capture energy from the surrounding environment, allowing the system to operate under different conditions. By using multiple energy sources together, the proposed model provides more reliable and continuously power in both urban and remote environments. The system performance is evaluated using simulated environmental data for different deployment scenarios. The results shows that the harvested energy is sufficient to support low-power IoT devices. Unlike, conventional systems, the proposed approach reduces the need for frequent battery replacement, which increases device lifespan and lowers maintenance requirements. The study demonstrates that hybrid energy harvesting is a practical and effective solution for autonomous Internet of things (IoT) applications. This work supports the development of self-powered, scalable, and environmentally friendly IoT networks, especially in locations that are difficult to access. Keywords Wireless Energy Harvesting(WSN), Internet of Things(IoT), Hybrid Energy Harvesting, Solar Energy, Vibration, Radio Frequency Energy, Self-Powered Iot, Energy Management.

Due to the rapid growth of the Internet of Things (IoT), researchers have demonstrated various IoT solutions, which are used to interconnect a wide range of IoT devices through the Internet. However, IoT stumbled into vertical silos; the available solutions provide specific IoT infrastructure, devices, protocols, data formats and models. This diversity and heterogeneity lead to interoperability issues. Heterogeneity happens at all IoT layers, especially at the application layer; devices often adopt mutually incompatible application-layer communication protocols to connect devices to IoT services. Furthermore, in order to integrate semantics to raw data, each system uses its one domain-specific ontology to make data more understandable and interpretable by adding semantic annotations. Working in isolation reduces the interoperability among IoT devices and systems, things across domains need to internetwork and collaborate to provide high level IoT services. Therefore, to alleviate the problem of both communication protocol interoperability and semantic interoperability across vertical silos of systems at the application layer, this paper proposes a semantic gateway (SGIoT) that acts as a bridge between heterogeneous sink nodes at the physical level and IoT services. SGIoT enables interconnectivity between communication protocols such as CoAP and MQTT regardless of their communication model, meanwhile it enables semantics integration throu gh cross-domain ontology (CDOnto) for semantic annotation, in order to provide interpretation of messages among IoT applications across domains. Our approach focuses on modularity and extensibility.

The secure boot-up and setup of Internet of Things (IoT) devices connected over the Cloud represent a challenging open issue. This paper deals with the automatic configuration of IoT devices in a secure way through the Cloud, in order to provide new added-value services. After a discussion on the limits of current IoT and Cloud solutions in terms of secure self-configuration, we present a Cloud-based architecture that allows IoT devices to interact with several federated Cloud providers. In particular, we present two possible scenarios, that is, single Cloud and a federated Cloud environments, interacting with IoT devices and we address specific issues of both. Moreover, we present several design highlights on how to operate considering real open hardware and software products already available in the market.

Internet of Things (IoT) have opened the door to a world of unlimited possibilities for implementations in varied sectors in society, but it also has many challenges. One of those challenges is security and privacy. IoT devices are more susceptible to security threats and attacks. Due to constraints of the IoT devices such as area, power, memory, etc., there is a lack of security solutions that are compatible with IoT devices and applications, which is leading this world of securely connected things to the “internet of insecure things.” A promising solution to this problem is going beyond the standard or classical techniques to implementing the security solutions in the hardware of the IoT device. The integration of emerging technologies in IoT networks, such as machine learning, blockchain, fog/edge/cloud computing, and quantum computing have added more vulnerable points in the network. This paper introduces a comprehensive study on IoT security threats and solutions. Additionally, this survey outlines how emerging technologies such as machine learning and blockchain are integrated in IoT, challenges resulted from this integration, and potential solutions to these challenges. The paper utilizes the 4-layer IoT architecture as a reference to identify security issues with corresponding solutions.

This chapter gives overview of Internet of Things (IoT), various issues in IoT and describes data management in IoT. IoT is emerging technology which interconnects things through the Internet. Things present in the surrounding are communicated and control the objects without human intervention. IoT helps in performing two way communications among various heterogeneous devices by using cloud storage and cloud computing. IoT mainly concentrates on communication, so the vast amount of data generated from plenty of devices is to be managed as it consumes lot of memory. Data management includes data processing techniques such as data filtering, aggregation, compression, data archiving. Various processing techniques eliminate the irrelevant data, reduce communication overhead and enhance bandwidth, storage space and Quality of service.

A review of the security vulnerabilities and countermeasures in the Internet of Things solutions: A bright future for the Blockchain

Smart agriculture with IoT (Internet of things) gives rise to agribusiness and may fulfill the demand of food in the world. Agribusiness will become more productive when IoT is introduced. As the farmers are becoming more aware to IoT, the possibility of introducing new technologies is gaining momentum in agribusiness. The IoT is highly efficient, accessible, persistent and of exposed nature. The farmers may use sensors for monitoring the crops, soil and also analyze the crop production. This will give boost up to precision agriculture. The information about farms like temperature, moisture level and soil mineral level, pH value of soil and air quality can be collected remotely by using IoT on smartphones or computer systems. Today’s IoT techniques and devices are so advanced and are mainly application dependent providing smart systems to be deployed in specific areas. In this paper, a review of IoT devices and protocols is presented and it also throws light on issues arise during the implementation of IoT in agriculture.

The Internet of Things (IoT) has had a considerable influence on our daily lives by enabling enhanced connection of devices, systems, and services that extends beyond machine-to-machine interactions and encompasses a wide range of protocols, domains, and applications. However, despite privacy concerns shown by IoT users, little has been done to reduce and protect individual information exposure. It is extremely difficult to mitigate IoT devices from reidentification threats which is why it is still a major challenge for IoT users to securely protect their information. The trust controls how we regulate privacy in our IoT platforms in the same way that it governs personal relationships. As IoT devices become increasingly linked, more data is shared across individuals, businesses, governments, and ecosystems. Technologies, sensors, machines, data, and cloud connections all rely largely on trust relationships that have been formed. With the rapid growth of additional types of IoT devices that are being introduced, it, therefore, expands privacy concerns and is difficult to develop trust with an IoT system or device without the option to regulate information privacy settings. Privacy has always been a barrier for many devices as they race for the early adoption of IoT technologies. Several Internet of Things devices or systems will continue to pose privacy threats. As a result, the main objective of this study was to examine the individual understanding of privacy and to promote information privacy protection awareness not only to IoT users but also to organizations that use IoT devices or platforms to run their day-to-day business operations. Furthermore, the objective extends to compare user knowledge and concerns about IoT privacy, as well as to identify any common attitudes and variances. However, in terms of enhancing individuals’ knowledge, an artifact was developed to educate and enhance information privacy awareness among IoT users. A pre- and postquestionnaire was generated to test and validate user knowledge regarding information privacy protection in IoT. The study was conducted using a quantitative research method. Findings indicate that IoT users’ awareness of information privacy protection turned out to be average, suggesting a need for education and awareness. Several participants stated that information privacy protection awareness is required within the community to educate, raise awareness, eliminate human error, and enable individuals to be conscious of their privacy when surfing the Internet.

The Internet of Things (IoT) devices is able to communicate with another IoT devices in heterogeneous environments. They are also able to create a network by their own using wireless capabilities without a centralized approach. This network is called wireless mobile ad hoc network (MANET). The MANET facilitate IoT devices to communicate with each other in an infrastructure less network of the Internet of Things environment. The IoT devices can dynamically join, create connection and exchange information among them. The role of cloud in this framework is to store and process the data by IoT devices. The communication Security has been raised as one of the most critical issues of cloud computing where resolving such an issue would result in a constant growth in the use and popularity of cloud. Our purpose of this study is to create a framework for providing the communication in an integrated framework of Cloud and MANET among IoT devices. Our main contribution links a new study that integrates cloud computing to the MANET and provides communication to the internet of things. This study can be used in the framework of the Internet of Things in future.

Water management in agriculture has been transformed by smart irrigation systems that use the Internet of Things (IoT) to maximize resource use and boost crop yields. IoT-based irrigation, which reduces waste and improves sustainability in the face of growing water scarcity, combines sensors, actuators and real-time data analytics to deliver accurate water flow. The use of IoT in agriculture is reviewed in this paper, which also covers AI-driven decision-making algorithms and communication technologies like LoRa, Zigbee and Wi-Fi. In agriculture, IoT has been widely employed in agriculture to enable better farming and redefine conventional practices. Some of the necessary applications include monitoring crops, monitoring livestock, automation of the supply of water through real-time data, promotion of optimal water consumption and wastage minimization. Furthermore, increased agricultural yields, cost savings and water conservation are just a few benefits of using IoT in irrigation systems. Research also claimed that when compared to traditional methods, IoT-based irrigation systems can save up to 30% on water usage. IoT-based irrigation has drawbacks despite its benefits, including costly upfront costs, complicated technology and cyber security threats. The use of self-powered sensors, AI-powered predictive irrigation and blockchain-enhanced data security are some of the upcoming trends. Smart irrigation systems have the ability to transform precision agriculture and guarantee both environmental preservation and food security by removing implementation obstacles. Future research should focus on enhancing interoperability among IoT devices, improving decision-making algorithms and developing cost-effective solutions for small-scale farmers. With continuous innovation and widespread adoption, IoT-driven smart irrigation has the potential to address global food security concerns while preserving water resources, creating a more sustainable and technologically advanced agriculture industry.

The Internet of Things (IoT) is a framework of interconnected computing devices mechanical and digital machines, internationally identifiable physical objects (or things) or people that are have unique identity and the ability to transfer data over a network without human-to-human or human-to-computer interaction., their combination with the Internet, and their representation in the digital world. The accessibility and availability of cheap components of IoT devices enables a extensive range of applications and provide smart environments. These devices perform actuating and sensing tasks and identified through unique addresses. The IoT devices are connected to the Internet and expected to use the Constrained Application Protocol (CoAP) at the application layer as a main web transfer protocol. Message Queuing Telemetry Transport (MQTT) does not enforce the use of a particular security approach for its applications, but instead leaves that to the application designer. Therefore, IoT solutions can be based on application context and specific security requirements. MQTT is a Client Server publish/subscribe messaging transport protocol. It is lightweight, open, uncomplicated, and designed to make implementation more easier. These characteristics of MQTT make it perfect for use in most of the situations, including communication in Machine to Machine (M2M) and Internet of Things (IoT). In IOT there is major use of Wireless Sensor Networks (WSN) which connects virtual world to physical world. In this paper focus is given to application layer of IOT. In application layer two important protocols are MQTT and CoAP. Security mechanism is proposed in the paper for these protocols.