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Vision and Challenges for Realizing the Internet of Things

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Abstract

Foreword by Peter Friess & Gérald Santuci: It goes without saying that we are very content to publish this Clusterbook and to leave it today to your hands. The Cluster of European Research projects on the Internet of Things – CERP-IoT – comprises around 30 major research initiatives, platforms and networks work-ing in the field of identification technologies such as Radio Frequency Identification and in what could become tomorrow an Internet-connected and inter-connected world of objects. The book in front of you reports to you about the research and innovation issues at stake and demonstrates approaches and examples of possible solutions. If you take a closer look you will realise that the Cluster reflects exactly the ongoing developments towards a future Internet of Things – growing use of Identification technologies, massive deployment of simple and smart devices, increasing connection between objects and systems. Of course, many developments are less directly derived from the core research area but contribute significantly in creating the “big picture” and the paradigm change. We are also conscious to maintain Europe’s strong position in these fields and the result being achieved, but at the same time to understand the challenges ahead as a global endeavour with our international partners. As it regards international co-operation, the cluster is committed to increasing the number of common activities with the existing international partners and to looking for various stakeholders in other countries. However, we are just at the beginning and, following the prognostics which predict 50 to 100 billion devices to be connected by 2020, the true research work starts now. The European Commission is decided to implement its Internet of Things policy for supporting an economic revival and providing better life to its citizens, and it has just selected from the last call for proposals several new Internet of Things research projects as part of the 7th Framework Programme on European Research. We wish you now a pleasant and enjoyable reading and would ask you to stay connected with us for the future. Special thanks are expressed to Harald Sundmaeker and his team who did a remarkable effort in assembling this Clusterbook.
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... be a product or equipment; in intelligent environments, it can refer to a tree, room, or building; in health systems, it can be an equipment that collects patient data. Taking into account this set of things that can be connected to the Internet, an IoT environment can be deployed in different domains such as healthcare, transportation and logistics, agriculture, security and home automation [1][2][3]. ...
... POX Controller: https:// github. com/ noxre po/ pox.3 Ryu Controller: https:// ryu-sdn. ...
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The significant adoption of the Internet of Things (IoT) has increased the challenges in providing adequate IoT infrastructures meeting essential requirements, such as dynamicity networks and low latency. In this context, the Software-Defined Networking (SDN) paradigm and the OpenFlow protocol provide new possibilities for IoT networks. Based on the global view of network elements enabled by the Controller, SDN allows the programmability and control of the infrastructure according to the actual demands of applications. The OpenFlow protocol defines the exchange of messages between controllers and switches, enabling communication and network control. OpenFlow implements three operation modes: proactive, reactive, and hybrid. Due to the dynamic characteristic of the IoT data stream, the reactive mode is mainly used and indicated for IoT environments. As the OpenFlow controller installs rules dynamically, there is no need to know the network’s sources, destinations, and paths in advance. Although reactive mode introduces dynamicity, it can generate additional delay due to switch-controller communication. This delay increases the response time of the IoT data stream. We propose an SDN-IoT scheduler based on Deep Neural Networks (DNN) to predict the time between data stream changes from IoT devices and install rules in advance, suppressing the existing delay in reactive mode. The proposal automatically uses previous data from the IoT data stream to calculate the time of the following communication from IoT devices. Our results indicate that predicting IoT data stream changes and installing OpenFlow rules in advance reduced about 51% of communications response time.
... By integrating smart sensors, RFID tags, and IoT-enabled devices, warehouses can automate labor-intensive tasks such as inventory counts, stock placement, and replenishment orders. This automation reduces the need for manual intervention and minimizes errors that can result from human oversight (Sundmaeker et al., 2018). In turn, automated processes enable faster decision-making and greater accuracy, which contributes to smoother operations and reduced downtime in warehouse activities. ...
Research
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The increasing adoption of Internet of Things (IoT) technologies and advanced computer vision systems is transforming inventory management in automated warehouses. This review explores how the integration of IoT and computer vision can enhance inventory accuracy and reduce discrepancies, which are critical challenges in modern supply chain operations. IoT-driven smart warehouses utilize interconnected devices such as sensors, RFID tags, and IoT gateways to provide real-time monitoring, tracking, and data transmission of inventory items. When paired with computer vision, which enables automated product recognition, counting, and anomaly detection, these systems can significantly improve operational efficiency and decision-making processes. This paper reviews key IoT components and their applications in smart warehouses, highlighting the role of computer vision in minimizing discrepancies and ensuring accurate inventory counts. We also examine case studies of IoT and computer vision integration in various industries, showcasing their combined potential to address challenges such as miscounts, misplaced items, and human error. Despite the benefits, this review also addresses challenges related to system integration, data management, and scalability. By analyzing current research and technological trends, this paper presents recommendations for enhancing the effectiveness of IoT and computer vision in inventory management and identifies opportunities for future innovations. Overall, this review emphasizes the transformative impact of IoT and computer vision on the warehousing sector, outlining how these technologies can lead to more accurate, efficient, and reliable inventory systems in the era of automation.
... This makes learning more alluring, energizing, and straightforward. It urges understudies to learn and remember the point for a drawn-out period [2]. It is a wellknown fact. ...
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With the growing progress and embracing of smart digital technology integration for education, large amount of data is collected from informative backgrounds which has been analyzed and given motivational perceptions to the educational worker. The data-driven method for improved understanding and enhancing knowledge together with the learning situation paves the way for learning analytics to contribute to smart learning. The current learning analytics lacks knowledge awareness, an essential component in smart education—this paper analysis the smart leaning mechanism and reviews the smart leaning application development tool. The survey has been taken based on the questionnaire related to smart learning with the respondents of 100 individuals. The paper also highlights the smart classroom integrated technology development towards smart learning architecture. The analysis includes the negative and positive impact of smart application-based learning and cost-effective leaning for the middle-income sectors.
... For perishable goods, IoT sensors can monitor temperature and humidity to maintain optimal storage conditions, minimizing spoilage. Automated alerts for low stock levels also streamline the replenishment process, reducing the need for manual checks and preventing excess inventory (Sundmaeker et al., 2010). ...
Chapter
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A Continuous innovation and the adoption of new technologies are crucial for merchants to develop a sustainable competitive edge. Technology-oriented toward customers signi cantly contributes to driving up revenues while reducing expenses, and more importantly, it plays a vital role in enhancing sustainability in retail operations. In this article, we take a cursory look at some of the most important retail technologies that have emerged in the recent past, as well as some technologies that are just starting to gain traction. We discuss the ways in which these technologies can assist retailers in adopting sustainable practices, such as reducing waste, optimizing energy usage, and improving inventory management, thereby enhancing the overall shopping experience for customers and promoting environmental stewardship.
... At that time, a Coke vending machine at Carnegie Mellon University in the United States was able to report inventory and temperature, becoming the first connected device [1]. In 1999, Professor Ashton proposed the concept of the "Internet of Things" [2,3]. After decades of development, the Internet of Things has become an important basic technology in the fields of smart grids, smart cities, smart medical care, internet of vehicles, and smart transportation [4]. ...
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The integration of smart contracts (SCs) within blockchain technology represents a pivotal direction in the evolution of the Internet of Things (IoT), enabling decentralization and enhancing user trust in the system. However, ensuring data privacy is a fundamental challenge that must be addressed during the deployment of these SCs. Many scholars have adopted data aggregation to protect privacy, but these methods are difficult to achieve fine-grained data collection. To this end, this paper proposes an efficient anonymous data collection (EADC) scheme suitable for the IoT environment. The scheme combines matrix algorithms with homomorphic encryption (HE) technology to effectively cut off the connection between users and data during data upload. In addition, the EADC scheme introduces a sophisticated data grouping protocol to improve the overall efficiency of the system. Analysis shows that the scheme can achieve efficient data collection without compromising user privacy.
... In particular, the Internet of things terminal not only has the requirements of narrowband communication and low-power computing, but also has the characteristics of large number and wide area distribution. In addition, the Internet of things application itself also has business diversity and particularity requirements [17], which makes the security protection of it different from the traditional human-oriented Internet security protection. The limitations of the traditional PKI certificate authentication technology in the Internet of things are gradually emerging. ...
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With the rise of the Internet of things, the limitations of traditional PKI certificate authentication technology have progressively emerged. Hence, identity-based public key algorithms have been proposed. In this paper, we propose a new approach to generate an identity key, named identity public key (IPK). IPK identity key generation protocol is based on SM2 elliptic curve cryptography and random matrix theory. It builds upon the concept of combined public key (CPK) and resolves the linear collusion issue of CPK as well as the authenticity verification problem of the declared public key of the simplified TF-CPK by enhancing the identity mapping approach. Another main aim of this paper is to prove the security of the IPK identity key generation protocol. Roughly speaking, we verify the security of each part of the private key and the security of the composite private key. We also increase the function and performance comparison with other schemes, such as IBC(SM9) and TF-CPK. Our scheme has the lowest computation cost, which demonstrates its rationality.
... IoT sensors, for example, can track the state of commodities in transit, thereby ensuring that perishable items are kept at the right temperature and so minimising waste and damage (Chukwudebe et al., 2021). IoT-driven data analytics also lets businesses proactively manage supply chain interruptions and precisely estimate demand (Sundmaeker et al., 2010, De Vass et al., 2020. IoT has strategic relevance in supply chain management since businesses are spending more and more on IoT solutions to acquire a competitive edge on the worldwide market (Aljabhan, 2022). ...
Preprint
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The rapid expansion of the Internet of Things (IoT) is revolutionising industries by enhancing connectivity among people, systems, and objects. With IoT device numbers predicted to rise from 9.7 billion in 2020 to 29 billion by 2030, its integration into supply chain management is increasingly critical, improving transparency, efficiency, and decision-making. This study focuses on evaluating the impact of IoT on supply chain efficiency within five Nigerian companies, a region where IoT's potential remains largely untapped due to infrastructural and technological challenges.Methods: The research employed a quantitative methodology, with purposive sampling used to select 50 participants across the 5 selected companies, ensuring a comprehensive assessment of IoT's influence across diverse sectors. A structured questionnaire was administered online to 10 senior managers from each selected company, collecting data on IoT adoption levels, applications, and impacts on supply chain performance. Data analysis was conducted using IBM SPSS version 27, employing descriptive analysis and regression and correlation tests to examine the relationship between IoT adoption and supply chain metrics.Results: The analysis revealed a significant adoption rate of 74.4% across the companies, with notable enhancements in supply chain metrics. Specifically, a negative correlation coefficient of -0.345 was observed between IoT adoption and lead time, although this was not statistically significant (p=0.053). Inventory turnover showed marked improvement, with 60% of companies reporting increased efficiency in inventory management. Order accuracy saw substantial improvements, with 17 out of 43 respondents (39.5%) rating it as significantly enhanced. Despite these positive trends, challenges such as inadequate infrastructure and high implementation costs were significant barriers, affecting the full realization of IoT benefits.Conclusion and Recommendations: The study concludes that while IoT adoption shows promise in enhancing supply chain operations in Nigeria, the benefits are unevenly realized, largely influenced by existing infrastructural deficits and high initial costs. Recommendations include enhancing digital infrastructure, developing supportive regulatory frameworks, and implementing pilot projects to better integrate IoT solutions tailored to specific operational needs. Investing in local expertise and fostering public-private partnerships are also critical for overcoming barriers to IoT adoption and leveraging its full potential for supply chain enhancement in Nigeria.
... b. Bluetooth, particularly with the advent of Bluetooth 5, offers improved range up to 100 meters and moderate data rates up to 2 Mbps [23], balancing low power consumption and ease of device pairing. It is widely used in wearable devices, health monitors, and personal area networks, though its limited range and data rates compared to Wi-Fi are notable constraints. ...
Chapter
In recent years, the rapid advancement of technology has revolutionized various sectors, including smart systems, energy, materials, and manufacturing. The convergence of the Internet of Things (IoT), Artificial Intelligence (AI), and Edge Intelligence has unleashed unprecedented potential, paving the way for innovative solutions that drive efficiency, sustainability, and economic growth. This book, "Advancing Innovation in Smart Systems, Energy, Materials, and Manufacturing: Unleashing the Potential of IoT, AI, and Edge Intelligence," is a testament to the transformative power of these technologies and their critical role in shaping the future. The genesis of this book lies in the growing recognition that traditional approaches to system design, energy management, materials science, and manufacturing are becoming increasingly inadequate in addressing the complex challenges of the modern world. As industries strive to enhance performance while reducing their environmental footprint, there is an urgent and compelling need for integrating smart technologies that can provide real-time insights, predictive capabilities, and adaptive responses. This integration not only optimizes processes but also drives innovation, leading to the creation of smarter, more resilient systems. Our exploration begins with an in-depth examination of IoT, a cornerstone of modern smart systems. IoT connects devices, systems, and services, enabling them to communicate and collaborate seamlessly. This connectivity facilitates collecting and analysing vast amounts of data, which can be harnessed to improve decision-making and operational efficiency. By embedding IoT into smart systems, we can create environments that are more responsive, adaptive, and efficient. Artificial Intelligence, another pivotal technology, brings a new dimension to smart systems. AI's ability to analyze data, recognize patterns, and make decisions allows for more intelligent and autonomous systems. In the context of energy, materials, and manufacturing, AI-driven solutions can predict maintenance needs, optimize resource allocation, and enhance product quality. This book delves into the ways AI can be leveraged to transform these sectors, highlighting both the opportunities and the challenges. Edge Intelligence, the practice of processing data closer to its source, complements IoT and AI by reducing latency and improving real-time decision-making. In manufacturing, for instance, edge intelligence can enable more responsive control systems that enhance production efficiency and product quality. In energy management, it can lead to smarter grids that balance supply and demand more effectively. The interplay of IoT, AI, and Edge Intelligence creates a powerful trifecta that is set to redefine the landscape of smart systems. Throughout this book, we have brought together insights from leading experts and practitioners across various fields. Their contributions reflect the latest research, innovative applications, and emerging trends in smart systems, energy, materials, and manufacturing. By showcasing real-world examples and case studies, we aim to provide a comprehensive understanding of how these technologies can be applied to address real-world challenges. I hope this book serves as a valuable and indispensable resource for researchers, engineers, policymakers, and anyone interested in the future of smart systems and technology. As we navigate the complexities of the modern world, it is imperative that we embrace innovation and leverage the full potential of IoT, AI, and Edge Intelligence. Together, we can build a future that is not only smarter and more efficient but also more sustainable and resilient
... However, the term "Internet of Things" did not become widely used until the early 2000s. The evolution of wireless communication technologies, miniaturization of sensors, and advancements in data processing capabilities were crucial for the proliferation of IoT applications [1][2][3]. After almost 20 years of development, a growing number of academics, business leaders, and government representatives tend to think that the Internet of Things is a crucial technology for raising our standard of living and living environments. ...
Chapter
The integration of mechatronics and the Internet of Things (IoT) has appeared as one of the most vital and transformative technologies in recent years. Mechatronics, a branch of engineering, blends the principles of mechanical, electrical, electronics, and computer engineering, while IoT, a new paradigm, has profoundly altered how one interacts with technology, information, and the environment. This assimilated technology has revolutionized smart manufacturing processes in industries, utilizing mechatronic systems, automated assembly lines, wireless networks, and data analytics to optimize the entire production process in real time. Building automated systems has become faster, more effective, and more reliable than ever before by fusing the concepts of mechatronics with the seamless connectivity and real-time data processing capabilities of the IoT. The immense potential of this integrated technology has empowered engineers, researchers, and innovators worldwide to harness the power of these two. This chapter will cover the foundation of IoT systems by leveraging the key concepts for designing IoT-based mechatronic system solutions. This chapter will further explore the recent advancements and innovative breakthroughs brought by IoT, with particular emphasis on the key enabling applications for smart homes, cities, factories, healthcare, agriculture, and vehicle systems. The book delves into the potential of IOT in connecting everything in our lives and its applicability to the real world.
Chapter
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