Adoption Of IoT Technologies Research Articles

IoT Applications in Agriculture: Enhancing Crop Yield in Vietnam

Purpose: To aim of the study was to analyze the IoT applications in agriculture: enhancing crop yield in Vietnam Methodology: This study adopted a desk methodology. A desk study research design is commonly known as secondary data collection. This is basically collecting data from existing resources preferably because of its low cost advantage as compared to a field research. Our current study looked into already published studies and reports as the data was easily accessed through online journals and libraries. Findings: IoT applications in agriculture have significantly enhanced crop yield in Vietnam. Through sensors and IoT devices, farmers monitor soil conditions like moisture, temperature, and humidity in real-time. This data-driven approach optimizes irrigation and fertilization, minimizing waste and maximizing resource efficiency. Studies show that smart farming techniques using IoT lead to higher crop yields by ensuring optimal growth conditions and timely pest and disease management. Remote monitoring also improves farm management, reducing labor costs and promoting sustainable practices through precise resource management. Unique Contribution to Theory, Practice and Policy: Technology acceptance model (TAM) & diffusion of innovations theory& resource-based view (RBV) may be used to anchor future studies on IoT applications in agriculture: enhancing crop yield in Vietnam. Encourage the adaptation and customization of IoT solutions to suit local farming practices and environmental conditions across different regions of Vietnam. Implement policies that incentivize the adoption of IoT technologies in agriculture, particularly among smallholder farmers.

Developing a causal framework of internet of things adoption barriers for agile manufacturing in post COVID-19

In order to remain competitive in a post-COVID-19 scenario, manufacturing organizations should use the pandemic scenario as a lever to make IoT adoption more agile and faster by reinventing their business models. Although, IoT has vast potential in multiple sensors’ direct integration without human intervention, its adoption has observed significant barriers during COVID-19. In this context, the current research aims to identify, prioritize, categorize, and investigate inter-dependencies among the significant barriers to adopting IoT technologies in the manufacturing industry. The analysis used two-stage integrated AHP-TOPSIS (Analytical Hierarchy Process-Technique for Order Preference by Similarity to Ideal Solution) and ISM (Interpretative Structural Modeling) techniques. For AHP and ISM techniques, a group of 8 experts from academia and industry with at least 10 years of experience was surveyed to capture their perceptions. Whereas, for TOPSIS, data were collected from 433 operational-level users. The research discloses that the significant driver barriers that hamper the adoption of IoT technologies are: poor internet infrastructure, high adoption & operating costs and lack of government regulations. This study will assist practitioners, decision-makers and organizations in understanding the significant barriers to seamless IoT implementation.

Smart Farming Revolution: Farmer’s Perception and Adoption of Smart IoT Technologies for Crop Health Monitoring and Yield Prediction in Jizan, Saudi Arabia

This study examines the perception and adoption of IoT technologies for crop monitoring among farmers in Jizan, Saudi Arabia. The research investigates the relationship between farmers’ awareness of IoT technologies, their perception of benefits, and willingness to adopt them. It also explores the influence of factors like access to information, training, and the perception of government support on adoption behavior. A structured questionnaire was distributed to 550 farmers, with a response rate of 90.91%. The analysis reveals a significant association between farmers’ awareness of IoT technologies and their perception of benefits. The perceived benefits show a moderate positive relationship with farmers’ willingness to adopt IoT technologies. Access to information, training, and the perception of government support also have a positive influence on adoption. The findings highlight the importance of increasing farmers’ awareness and providing access to information and training on IoT technologies. The study emphasizes the need for government support in facilitating adoption. Recommendations include exploring additional factors, conducting longitudinal studies, and developing tailored training programs. Collaboration among stakeholders and financial support mechanisms is also crucial. This study contributes to the understanding of IoT technology adoption in agriculture, providing insights for policymakers, agricultural extension agencies, and technology providers. By embracing IoT technologies and implementing the recommended actions, farmers in Jizan can enhance their crop monitoring practices, improve productivity, and promote sustainable farming.

Performance Assessment and Mitigation of Timing Covert Channels over the IEEE 802.15.4

The fast development and adoption of IoT technologies has been enabling their application into increasingly sensitive domains, such as Medical and Industrial IoT, in which safety and cyber-security are paramount. While the number of deployed IoT devices increases annually, they still present severe cyber-security vulnerabilities, becoming potential targets and entry points for further attacks. As these nodes become compromised, attackers aim to set up stealthy communication behaviours, to exfiltrate data or to orchestrate nodes in a cloaked fashion, and network timing covert channels are increasingly being used with such malicious intents. The IEEE 802.15.4 is one of the most pervasive protocols in IoT and a fundamental part of many communication infrastructures. Despite this fact, the possibility of setting up such covert communication techniques on this medium has received very little attention. We aim to analyse the performance and feasibility of such covert-channel implementations upon the IEEE 802.15.4 protocol, particularly upon the DSME behaviour, one of the most promising for large-scale time critical communications. This enables us to better understand the involved risk of such threats and help support the development of active cyber-security mechanisms to mitigate these threats, which, for now, we provide in the form of practical network setup recommendations.

A federated collaborative recommendation model for privacy-preserving distributed recommender applications based on microservice framework

The wide adoption of IoT technologies has accelerated the accumulation of big data. Recommender systems (RS) is one of the most effective methods to extract user interested items from the huge volume of big data. However, implementing a recommender system over the distributed error-prone IoT devices faces two challenges. On the one hand, the distributed IoT devices may randomly fail to deliver its local data due to hardware malfunction, which may cause unavailability of the recommender system. Moreover, collecting the raw data from the distributed IoT devices may cause data privacy leakage issue, since the privacy data of user-item interaction records may be abused by vicious parties. In view of these challenges, we propose a federated collaborative recommendation model based on microservice framework in this paper to implement privacy preserving distributed recommendation applications. Firstly, we utilize the federated learning framework to train the collaborative recommendation model, where the raw data on each distributed device is kept locally and only item related model parameters are exposed to train the federated recommendation model. Moreover, we adopt the microservice framework to encapsulate different functions of the federated recommender model. Each distributed device can participate in the federated training process via service registration and service discovery function of the microservice framework. Furthermore, we enhance the typical Neural Collaborative Filtering model with the proposed FedNeuMF model by fusing auxiliary user profiles and item attributes to improve the recommendation accuracy. Finally, we conduct a set of experiments on three real-world datasets to check the performance of our proposal.

Digitalization and Industrial Revolution 4 (IR4) Technologies

With the advent of the Industrial Revolution 4 (IR4), many new challenges have emerged. One such issue is privacy and security. Millions of devices are now connected to the internet, and there is no concrete way to ensure that the user has authority (or) control over its data. This study addresses this challenge by drawing a theoretical framework for IoT software that can provide mathematical proof to the user regarding the privacy of the data. Such a certification would ensure that the data remains confidential as well as it will accelerate the rate of adoption of IoT technologies.

Towards a Maturity Model for IoT Adoption by B2C Companies

The fast-growing market for the adoption of IoT technologies poses serious challenges for companies providing IoT solutions. These challenges require constant technological and managerial improvement from the companies. To select the right direction for improvements, managers need appropriate tools for analysis and decision making. Recognised tools of this type are maturity models. Currently, maturity models developed for IoT adoption are mainly oriented to the business to business (B2B) market, while business to consumer (B2C) companies also need such a reliable tool for business improvement. Thus, this work is intended to fill the gap in existing research through the development of a maturity model for IoT adoption focused on the B2C market. To achieve this goal, we based our model on the scientific literature as well as on practical experience gained by leading companies in the market of IoT solutions. Moreover, the development and validation of the maturity model are carried out in close collaboration with two reputable European experts with extensive practical experience in this field. The result is a maturity model, which is a balanced, practice-oriented tool for assessing the maturity of the IoT solutions implementation and accounting for the specificity of the B2C market.

Ne Kadar Hazırız? Nesnelerin İnterneti Teknolojilerinin (IoT) Tüketiciler Tarafından Kabulü

The aim of this study is to determine the factors that are important in the acceptance of Internet of Things technologies by consumers and to establish a model that explains the acceptance behavior. With data collected from 359 participants, the model is tested using partial least square structural equation model. Accordingly, 62% of behavioral intention is explained. In this context, some relationships are defined for the first time within the scope of the present study and presented to the literature. Results show how complex the formation of consumer intention is for the adoption of IoT technologies.

IoT based smart solar energy monitoring systems

Today our society needs more energy for day-to-day activities due to rapid globalization and industrialization. In order to minimize the stress and dependency on fossil fuel, the most sustainable way is to harness suns energy. Solar energy is characterized by low cost, environment friendly, does not require frequent maintenance and most importantly, negligible maintenance cost. However, there is a requirement of monitoring solar installation in order to maximize the output power by setting real-time angles with the suns position. This can be easily done by the adoption of IoT technologies. The Internet of Things is often utilized in the measurement of solar energy for efficiency. It's also utilized to maintain the solar plant's health. The cost of renewable energy technology is decreasing throughout the globe, which encourages the construction of large-scale solar plants. Automation of plant observation on such a large scale of preparatory deployments requires sophisticated systems reliant on Internet connections since the majority of field units are situated in isolated, remote locations and therefore are not overseen from a central office. The project is based on the use of the most up-to-date, cost-effective method for remotely monitoring a solar plant performance by the inclusion of IoT. It can assist with plant maintenance, problem diagnostics, and real-time monitoring.

Using UTAUT Model to Determine Factors Affecting Internet of Things Acceptance in Public Universities

This article aims to review the influencing factors and their relationships to the adoption of IoT technologies in the education domain among undergraduate students in Saudi public universities. The purpose of this study is to propose a framework using UTAUT to increase IoT acceptance. Previous studies found that performance expectancy, effort expectancy, social influence, and facilitating conditions have significant predictors of IoT acceptance. However, other studies found that not all UTAUT variables are significant predictors of IoT acceptance such as effort expectancy. There are three research gaps identified through previous studies, field issues, and theory and model. First, there is a lack of studies in consumers’ adoption of IoT technologies. Second, there is a lack of user acceptance of IoT technologies. Third, there is a lack of confident and uncertainty caused by new technologies. A quantitative method approach will be used. The online questionnaire survey well be sent to 300 undergraduate students of the selected public university. The Partial Least Square-Structural Equation Modelling (PLS-SEM) will be used to analyse the collected data.

Impact of IoT Technologies on Smart City Infrastructure: Current Applications and Future Potential

With the advent of digitization, upcoming technologies like Internet of Things (IOT) are being used by organizations to manage their business, infrastructure as well as assets. In order to make the IT Infrastructure more efficient, upcoming technologies like Internet of things play a very important role as IoT has increased the scale of the storage and the server spaces, improved the internet connectivity thereby leading to a smarter IT infrastructure. Although IoT adoption is taking place rapidly at the enterprise and industrial level; there is a dearth of academic literature in this area. Hence the objective of the paper is to study the adoption of various IoT technologies for smart city infrastructure, understand the impact/benefits of these technologies and propose future potential applications which can be used for smart infrastructure. A case study approach has been adopted for this research wherein various use cases in the IT industry have been analysed with respect to the adoption of IoT technologies 0066or smart city infrastructure and the benefits of the same to the various sectors. The study will be useful for academicians, and practitioners, and Government officials to design and develop solutions for smart city infrastructure that will add to wellbeing of society at large.

ASSESSING OF THE EFFECTIVE FACTORS IN THE ACCEPTANCE OF INTERNET OF THINGS TECHNOLOGY IN SMART BUILDINGS (CASE STUDY: CUSTOMER OF ACTIVE COMPANIES IN SMART BUILDINGS IN TEHRAN)

The purpose of this research is to investigate the relationship between effective factors in accepting Internet technology of objects in intelligent building. This research is based on the goal of the research is applied. The information is collected through a descriptive survey. The statistical population of this research includes all active companies in the field of intelligent building. Samples were randomly selected from 60 companies. The data of the present study were collected through interviews and a questionnaire (Davis standard). This questionnaire has 23 questions. The results of the research show that beneficial understanding has a positive effect on the adoption of IoT technologies in intelligence building , Understanding the ease of use has a positive impact on the adoption of IoT technologies in intelligence building , Understanding the ease of use has a positive impact on understanding the usefulness of IoT technologies in intelligence building , Trust has a positive impact on the adoption of IoT technologies in intelligence building , trust has a positive impact on the understanding of the usefulness of IoT technologies in intelligence building , Social influences have a positive impact on the adoption of IoT technologies in intelligence building. Good perceptions have a positive impact on the adoption of IoT technologies in intelligence building; understanding behavioral control has a positive impact on the adoption of IoT technologies in intelligence building.