Low Cost Integration of IoT Technologies for Building Automation

This study aims to analyze the use of Internet of Things (IoT) technology in the novel "Hujan" by Tere Liye. This novel shows how the love story and life struggle of the main character, Lail, are connected to the development of IoT technology. This research aims to understand how IoT technology shapes the story from the aspect of the situation to the characteristics of the related IoT devices. Through the hermeneutic method, this research identifies the use of IoT in several contexts. The findings obtained in the novel are 1) Smart Buildings, 2) Smart Farming, 3) Smart Home, 4) Smart City, and 5) Smart Healthcare. The results show that IoT technology is a key element in achieving a more advanced and connected digital society, bringing positive impacts in daily life and providing smart solutions to various global challenges.

Major advances in the Internet of Things (IoT) technologies are offering unprecedented automated services to various sectors. IoT has shown great promise in transforming buildings and institutions into smart buildings and institutions, making traditional task management more efficient. In particular, there has been remarkable progress in successfully integrating IoT into various contexts, such as smart homes, businesses and cities. Success in such technological transformations is not only due to the proper deployment and implementation of IoT but also to the effective employment of related technologies, such as big data and cloud computing technologies, and making informed decisions on the inclusion of the required hardware and software for all the elements involved in the IoT environment. While a significant amount of IoT research in various contexts has been proliferated in recent years, attention given to its deployment for linguistic landscapes (LLs) is still very rare. The aim of this paper is to propose a smart Al-Noor Mall LL which takes into account the appropriate deployment of IoT tools and relevant technologies. The paper also thoroughly discusses the background of the field, covering IoT technologies, cloud computing, and big data studies, followed by a review of the recent publications involving the successful deployment of IoT technologies combined with big data and cloud computing in various contexts. The literature also covers the success factors that contribute to the robustness of the required real-time operating system (RTOS) in an IoT-based environment in order to enable IoT devices to manage their resources efficiently. Based on a detailed analysis of the literature, a three-level framework (i.e. the object, communications and application levels) together with the elements that are required for IoT-based smart LL solutions is proposed. A case study of Al-Noor Mall is used to validate the proposed framework and the results indicate that IBM Bluemix can help Al-Noor Mall management and customers to locate any particular shop in the huge shopping mall, which thereby makes the customers’ shopping experience more satisfying. Finally, the challenges (i.e. energy efficiency, security, and intelligent data analysis) facing the successful deployment of IoT technologies are discussed with proposals for future research directions in the IoT research field.

Smart city is a city that increases the interactivity of its components and put emphasis on their functionality. Internet of Things technology (IoT) is an innovative solution in environmental protection. Usually, information on air quality is very scattered. This paper describes the test stages of pre-implementation works, focusing on the presentation of the technical design of the measurement nodes and the assumptions of the IT project. The goal of the project Intelligent Wireless Sensor Network Infrastructure (IIBSC) is, among others, to create a dense network of air quality measurement nodes at city, district or even street level. The concept is based on Internet of Things (IoT) technology using a matrix construction tool connected to multiple identical measurement nodes located in the test area. The project developed a hardware platform supporting sensors and resistant to external factors, and an ISIMPIO information platform based on edge processing technology for processing data from air quality sensors. Due to the use of Internet of Things (IoT) technology, an edge server using edge processing was designed. Edge server provides a complete ecosystem for building edge applications that are fully optimized for seamless field work. In addition, it allows the implementation of integrated Python software, the MQ Telemetry Transport support protocol (MQTT), time-series database, firmware update over a wireless network, and built-in security system. Measuring the concentration of particulate matter and other substances in the air will be useful for specialists assessing their dynamics. The technology and test installation selected corresponds to the leading solutions in this field in Europe and, in the future, should also be extended to less urbanised areas.

In these days, a single search on Google Scholar using the expression Internet of Things (IoT) brings almost 3 520 000 results. Since 1999, when Kevin Ashton used the expression Internet of Things for the first time as the title of a presentation he made at Procter & Gamble, it has received more and more attention from academics, IT experts, the popular press, and the companies in general. All this attention is due to the fact that the IoT technologies are transforming the way in which companies work and do business. Two of the promising domains of the IoT technology are intelligent building and workplace management. In these days, the workstation became the second companies’ largest expense just after the payroll. Therefore, the development and implementation of IoT technology contribute to the optimization of buildings (energy saving, temperature, and air conditioning control, etc.) and workplaces (occupation rates, etc.), and has the potential to change the major patterns of the corporate real estate. As a result, integrating IoT technology in the workplace management is a strategic challenge in order to create value for the company through supporting strategic decisions, investments and workers’ productivity. The purpose of this work is to review the literature dedicated to IoT and workplace management, in order to identify relevant issues and knowledge concerning the relationship between the IoT technologies (e.g. RFID, sensor, actuator, smart item) and a building on the optimization of the workplace and the productivity of its occupants. The literature review is the best approach to the appropriation of a subject once it allows using the ideas developed in the literature to justify a particular approach to the topic, the selection of methods and demonstration of the relevance and possible contributions (Hart, 1998). This work will also present a discussion of future research directions and the principal challenges related to the IoT and workplace productivity.Purpose: A paper review of well-known journals publishing research on the subject “IoT and workspace management” from the last 10 years.Design/methodology/approach: We will follow the approach proposed by Levy and Ellis (2006) to conduct an effective literature review. We also will lean on the work of Mishra et al. (2016) that identified the most relevant authors on the IoT literature in order to identify those studies/authors relating IoT technology and workspace productivity.

The Internet of Things (IoT) environment is constantly evolving. Many IoT services have emerged, improving living conditions. Smart homes were among the first developments, and smart buildings, smart factories, and smart cities are attracting increasing attention. Smart cities represent the ultimate convergence of the IoT, the Cloud, big data, and mobile technology. Smart homes, buildings, and factories create smart cities. In addition, the IoT finds applications in traffic control, public safety, and medical services, permitting group-based communication. As the scale of service grows, the number of things (devices) constituting the service also increases. However, security vulnerabilities arise in group-based communication environments. A device may require authentication when entering a gateway; to secure environments with large numbers of devices (such as those featuring IoT smart metering), the gateways bear heavy loads. Therefore, efficient authentication of group leaders and devices is essential. Here, we develop a dynamic group authentication and key exchange scheme for group-based IoT smart metering environments which enables efficient communication among secure IoT services. Our group authentication scheme increases the computational efficiency of the group leader and the participating devices, based on a threshold secret sharing technique.

When the large amount of Distributed Generations (DGs) are connected to the grid, the whole distributed power network lost line, and the voltage fluctuates are obvious. In recent years, the concepts of power Internet of Things (IoT)technology and energy Internet are proposed. Therefore, power grid technology has entered a new stage. The IoT technology is characterized by high bandwidth, high transmission rate, and low latency. In addition, with the collected data are increased, IoT becomes an effective way to improve the computing power of edge nodes in edge computing. In order to reduce network losses and voltage fluctuations, reactive power optimization is need to be implement in distribution network system. This paper proposes a distributed power voltage regulation strategy based on the particle swarm optimization and deep belief network (PSO-DBN) under the IoT. Firstly, IoT technology and characteristics are introduced, and the current research status of voltage regulation technology are analyzed in distribution network. Secondly, the weight of DBN is improved with PSO. Finally, the IEEE33 bus system is taken as a simulation case, the effects of daily reactive power optimization and the amount of historical data is analyzed. It is concluded that the method proposed in this paper has obvious effects on reducing voltage fluctuation and network loss. KeywordsDistributed generationIoTPSO-DBNReactive power optimization

Initially, the concept of Smart Cities (urban settlement) originated from the Internet of Things (IoT) technology, however, the use of IoT technology can be extended to the concept of Smart Villages (rural settlement) as well, improving the life of the villagers, and the communities as a whole. Yet, the rural settlements have slightly different requirements than the urban like settlements. If application of IoT in Smart Cities can be characterized by densification of IoT to day-to-day life, following cities’ structural characteristics of being densely settled places, IoT empowered Smart Villages are usually a system of dispersion and deficiency. In this manner, this research paper will address and discuss different application areas of IoT technology, identifying differences, but also similarities in both ecosystems, while trying to illuminate the standardization efforts that can be applicable in both contexts. In our text we will propose the following IoT application domains, which will also serve as a base for research on smart villages: 1. Natural Resources and Energy, 2. Transport and Mobility, 3. Smart Building, 4. Daily Life, 5. Government, and 6. Economy and Society. By providing an overview of technical solutions that support smart solutions in Smart Cities and Smart Villages this research paper will evaluate how, with IoT empowered Smart Villages and Smart Cities, an overall improvement of quality of life of their inhabitants can be achieved.

The Internet of Things (IoT) technology will soon become an integral part of our daily lives to facilitate the control and monitoring of processes and objects and revolutionize the ways that human interact with the physical world. For all features of IoT to become fully functional in practice, there are several obstacles on the way to be surmounted and critical challenges to be addressed. These include, but are not limited to cybersecurity, data privacy, energy consumption and scalability. The Blockchain decentralized nature and its multi-faceted procedures offers a useful mechanism to tackle several of these IoT challenges. However, applying the Blockchain protocols to IoT without considering their tremendous computational loads, delays, and bandwidth overhead can let to a new set of problems. This review evaluates some of the main challenges we face in the integration of Blockchain and IoT technologies and provides insights and high level solutions that can potentially handle the shortcomings and constraints of both IoT and Blockchain technologies.

Internet of Things (IoT) technologies are undeniably already all around us, as we stand at the cusp of the next generation of IoT technologies. Indeed, the next-generation of IoT technologies are evolving before IoT technologies have been fully adopted, and smart dust IoT technology is one such example. The concept of smart dust IoT technology, which features very small devices with low computing power, is a revolutionary and innovative concept that enables many things that were previously unimaginable, but at the same time creates unresolved problems. One of the biggest problems is the bottlenecks in data transmission that can be caused by this large number of devices. The bottleneck problem was solved with the Dual Plane Development Kit (DPDK) architecture. However, the DPDK solution created an unexpected new problem, which is called the mixed packet problem. The mixed packet problem, which occurs when a large number of data packets and control packets mix and change at a rapid rate, can slow a system significantly. In this paper, we propose a dynamic partitioning algorithm that solves the mixed packet problem by physically separating the planes and using a learning algorithm to determine the ratio of separated planes. In addition, we propose a training data model eXtended Permuted Frame (XPF) that innovatively increases the number of training data to reflect the packet characteristics of the system. By solving the mixed packet problem in this way, it was found that the proposed dynamic partitioning algorithm performed about 72% better than the general DPDK environment, and 88% closer to the ideal environment.

The Blockchain technology provides a way to record transactions or any digital interaction that is designed to be secure, tamper-proof, transparent, highly resistant to outages, traceable and auditable. The Internet of Things (IoT) technology is able to link computing devices, mechanical and digital machines, objects, animals or people that are provided with unique identifiers (UIDs) and provides the ability to transfer data over a network without requiring human-to-human or human-to-computer interaction. These features encourage us to explore the combined application of IoT and Blockchain-based technology. In this paper, we propose a system architecture of blockchain and IoT based intellectual property protection system, which can process three types of intellectual property: 1) Patents, Copyrights, Trademarks etc.; 2) Industrial design, Trade dress, Craft works, Trade secrets etc.; and 3) Plant variety rights, Geographical indications etc. Using blockchain P2P network and IoT devices, the system can help us to establish a trusted, self-organized, open and ecological intellectual property protection system. To the best of our knowledge, this is the first work that applying blockchain technology and IoT technology on traditional intellectual property protection and trade ecosystem.

The idea to connect everything to anything and at any point of time is what vaguely defines the concept of the Internet of Things (IoT). The IoT is not only about providing connectivity but also facilitating interaction among these connected things. One of the most significant concerns of IoT is to provide security assurance for the data exchange because data is vulnerable to some attacks by the attackers at each layer of IoT. The IoT has a layered structure where each layer provides a service. The security needs vary from layer to layer as each layer serves a different purpose. This paper aims to analyze the various security and privacy threats related to IoT. Some attacks have been discussed along with some existing and proposed counter measures. In developing countries, IoT technologies have brought increased efficiency and effectiveness to existing processes. For instance, farmers are using remote sensors to monitor moisture levels and soil conditions in the fields to avoid crop failure. Similar sensors are providing remote control of micro-irrigation pumps for example in India and water pumps in Rwanda, improving functionality and reducing repair intervals. And in Haiti, healthcare professionals are using “smart” thermometers to better track vaccine delivery and storage. Totally the paper presents an overview of the enablement of IoT in developing countries and discusses the visions, general applications, opportunities and challenges of IoT in these countries. It also touches on issues relating to security, privacy, trust and the accompanied complexity. The potential applications for IoT are countless and can optimize processes with a direct impact on society. Certain challenges have to be addressed to make IoT deployment successful. It will be shown that some of the challenges can be turned into opportunities and that IoT has good chances to succeed in developing countries. This report explores the current use and potential of Internet of Things (IoT) technologies in tackling global development challenges, highlighting a number of specific instances where IoT interventions are helping to solve some of the world’s most pressing issues it presents summary conclusions on what is required for the IoT to reach billions of people living in the developing world, and also to accelerate income growth and social development as a result.

Participation and inclusion in the business ecosystem have emerged as a growing trend for company collaboration in areas such as innovation, product development, and research. Collaborations can take many forms, ranging from the traditional value chain to strategic alliances, corporate networks, and digital ecosystems. The Internet of Things (IoT) and Big Data Analytics (BDA) play key roles in developing smart tourism destinations by delivering efficient management solutions, increased public safety, and improved operational efficiency while managing different risks and challenges, while also being a source of such risks and challenges. The objective of this article was to investigate the potential of IoT and BDA to properly control the risks associated with participants in a tourism destination’s digital ecosystem. The authors used the systematic literature review (SLR) method to examine scientific and applied articles on this subject. As a result, the main risks of the digital tourism ecosystem (DTE) as a whole and of the IoT and BDA technologies used in it were identified and classified; the features of DTE that affect risk management in it were distinguished; IoT technologies and their applications used in DTE were outlined; and the roles of DTE participants and the possible IoT technologies that can successfully address the risks associated with a given role were defined.

The traditional resource sharing method allocates resources according to their importance and node weight ranking, which leads to uneven distribution of node loads and resource allocation with less efficiency and high energy consumption. In order to solve the above problems, the method of resource allocation of college ideological and political education based on Internet of Things (IoT) technology is studied. The IoT technology is used for establishing the communication Internet of Things or for sharing college ideological and political education resources, and the MCTS algorithm is used to search for college ideological and political education resources. For the case of education resources in colleges and universities, according to the simple semantic reasoning for establishing the mapping relationship between education resources and distribution of nodes, we realise the allocation of resources for education. The test experiment results show that the researched resource allocation method has low allocation delay and reduces at least about 23.7% of energy consumption, which is more effective.

Nowadays, monitoring health systems in robust technology has been extensively applied in the sports field. Even though massive utilization of wearable device technologies aims to quantify athlete performance, inconsistent performance still exists between training sessions and competition. The rigorous discussion about the latest research in monitoring technological systems will help trainers obtain accurate data about athlete performance. This paper focuses on the athlete monitoring system in terms of psychological and physiological parameters and applications in individual sports based on Internet of Things (IoT) Technology. The study incorporates three factors: the parameters that affect athlete performance, multiple device sensors in sports health monitoring, and IoT technology’s application for athletes. Based on analysis and observation, efficient sports health monitoring can effectively enhance athlete performance in physiological and psychological conditions. An IoT system encompasses four main aspects: sensing, networking, data processing and application layer. These aspects provide real-time information on the athlete’s body condition during training and games. Therefore, this monitoring system greatly assists coaches in designing practical training and activities for athletes. It is highlighted that wearable health monitoring systems by IoT technology will be further built based on athlete requirements.

This article explores methods for optimizing energy consumption in smart buildings using big data analysis and Internet of Things (IoT) technology. The research initiates with the extraction of pivotal attributes-including time, ambient temperature, humidity levels, and illumination intensity-via the processes of data cleansing and preparation. Following this, both descriptive and inferential statistical methodologies are applied to investigate the interplay between energy usage and a range of contributing elements. For predicting future energy consumption patterns of structures, the investigation employs the Nonlinear Autoregressive (NAR) neural network approach alongside the Long Short-Term Memory (LSTM) network to develop a predictive model. Central to this endeavor is the Intelligent Energy Management System (IEMS), which harnesses AI and machine learning (ML) techniques to facilitate real-time surveillance, precise forecasting, and smart optimization of a building's energy consumption metrics. By leveraging IoT technology, the IEMS gathers consumption data, applies advanced big data analytics combined with ML algorithms for processing and interpretation, and devises optimal strategies for energy utilization predicated on forecast outcomes and external influences. Empirical findings indicate that the deployment of these optimization tactics has led to a reduction in overall building energy consumption by approximately 20.35 %, with the most pronounced effect observed in air conditioning energy use, which saw a decrease of 25.23%. This research shows that the intelligent building energy consumption management system combining big data analysis and IoT technology has remarkable effects in improving energy utilization efficiency and reducing energy consumption, which provides strong technical support and practical reference for energy consumption optimization of intelligent buildings in the future.