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In this paper, we present an implementation work of sensing and actuation capabilities for IoT devices using the oneM2M standard-based platforms. We mainly focus on the heterogeneity of the hardware interfaces employed in IoT devices. For IoT devices (i.e., Internet-connected embedded systems) to perform sensing and actuation capabilities in a standardized manner, a well-designed middleware solution will be a crucial part of IoT platform. Accordingly, we propose an oneM2M standard-based IoT platform (called nCube) incorporated with a set of tiny middleware programs (called TAS) responsible for translating sensing values and actuation commands into oneM2M-defined resources accessible in Web-based applications. All the source codes for the oneM2M middleware platform and smartphone application are available for free in the GitHub repositories. The full details on the implementation work and open-source contributions are described.

In recent years, the Internet of Things (IoT) has not only become ubiquitous in daily life but has also emerged as a pivotal technology across various sectors, including smart factories and smart cities. Consequently, there is a pressing need to ensure the consistent and uninterrupted delivery of IoT services. Conformance testing has thus become an integral aspect of IoT technologies. However, traditional methods of IoT conformance testing fall short of addressing the evolving requirements put forth by both industry and academia. Historically, IoT testing has necessitated a visit to a testing laboratory, implying that both the testing systems and testers must be co-located. Furthermore, there is a notable absence of a comprehensive method for testing an array of IoT standards, especially given their inherent heterogeneity. With a surge in the development of diverse IoT standards, crafting an appropriate testing environment poses challenges. To address these concerns, this article introduces a method for remote IoT conformance testing, underpinned by a novel conceptual architecture termed CLOCIS. This architecture encompasses an extensible approach tailored for a myriad of IoT standards. Moreover, we elucidate the methods and procedures integral to testing IoT devices. CLOCIS, predicated on this conceptual framework, is actualized, and to attest to its viability, we undertake IoT conformance testing and present the results. When leveraging CLOCIS, small and medium-sized enterprises (SMEs) and entities in the throes of IoT service development stand to benefit from a reduced time to market and cost-efficient testing procedures. Additionally, this innovation holds promise for IoT standardization communities, enabling them to champion their standards with renewed vigor.

As the Internet of Things (IoT) revolution presents an enormous opportunity for all industry verticals ranging from startups to large enterprises to create new types of services, standard bodies and global alliances have been working on establishing common standards for IoT systems. The oneM2M is the global partnership developing standards for Machine-to-Machine (M2M) communications and the Internet of Things. It develops technical specifications for the globally-applicable, interoperable common M2M/IoT service layer platforms, which play a pivotal role in building the ecosystem driven by key players, including developers and consumers. In this paper, we analyze the oneM2M standards, and introduce Mobius and &Cube, which are oneM2M-compliant M2M/IoT software platforms for servers and devices, respectively. We also present four pilot services using the platforms and several prototype IoT devices. Finally, we discuss three aspects, advanced discovery, open API, and peer-to-peer that are required for the oneM2M to build IoT ecosystem by attracting developers and consumers into the emerging IoT ecosystem.

This chapter explores the evolution of the transport industry and apply lessons from the telecom industry to revolutionize the transport experience for its users. In the 1980s, the Transport and Road Research Laboratory (TRRL) independently developed traffic responsive coordinated systems in cooperation with other governmental and industry players. This system later morphed into two competing proprietary solutions known as Split Cycle Offset Optimization Technique (SCOOT) in the United Kingdom and Sydney Coordinated Adaptive Traffic System (SCATS) in Australia. SCOOT and SCATS have been successfully deployed in many cities around the world. The chapter presents oneTRANSPORT project as a case study that is an Innovate UK‐supported project initiative in the area of “Integrated Transport‐In‐Field Solutions”. The project addresses both immediate and anticipated future challenges facing the transport industry. The oneTRANSPORT solution is based on oneM2M, an international standard to truly enable the Internet of Things (IoT) revolution.

This chapter introduces basic concepts related to Internet of Things (IoT) data privacy, and discusses the approaches to IoT data privacy. It then describes the Privacy Preference Manager (PPM), which is an IoT data platform component that can provide data privacy by registering users’ consent and privacy preferences, providing a way to modify or update them, providing rules for data flow according to users’ preferences, and recording all transactions. Next, the chapter discusses how the emergence of IoT is impacting data privacy, and describes some existing approaches to address both online‐ and IoT‐related privacy. It further provides information on a generalized personal data handling architecture for IoT that fulfills the requirements identified along with a description of how this has been realized by the oneM2M IoT platform standard and in particular its PPM component.

Like what happened to the Internet of Things (IoT), smart cities have become abundant in our lives as well. One of the smart city definitions commonly used is that smart cities solve city problems to enhance citizens’ life quality and make cities sustainable. From the perspective of information and communication technologies (ICT), we think this can be done by collecting and analyzing data to generate insights. The City Data Hub, which is a standard-based city data platform that has been developed, and a couple of problem-solving examples have been demonstrated. The key elements for smart city platforms have been chosen and they have been included in the core architecture principles and implemented as a platform. It has been proven that standard application programming interfaces (APIs) and common data models with data marketplaces, which are the keys, increase interoperability and guarantee ecosystem extensibility.

An aging population and human longevity is a global trend. Many developed countries are struggling with the yearly increasing healthcare cost that dominantly affects their economy. At the same time, people living with old adults suffering from a progressive brain disorder such as Alzheimer’s disease are enduring even more stress and depression than those patients while caring for them. Accordingly, seniors’ ability to live independently and comfortably in their current home for as long as possible has been crucial to reduce the societal cost for caregiving and thus give family members peace of mind, called ‘aging in place’ (AIP). In this paper we present a way of building AIP services using standard-based IoT platforms and heterogeneous IoT products. An AIP service platform is designed and created by combining previous standard-based IoT platforms in a collaborative way. A service composition tool is also created that allows people to create AIP services in an efficient way. To show practical usability of our proposed system, we choose a service scenario for medication compliance and implement a prototype service which could give old adults medication reminder appropriately at the right time (i.e., when it is time to need to take pills) through light and speaker at home but also wrist band and smartphone even outside the home.

Software Defined Networking represents a mature technology for the control of optical networks, though all open controller implementations present in the literature still lack the adequate level of maturity and completeness to be considered for (pre)-production network deployments. This work aims at experimenting on, assessing and discussing the use of the OneM2M open-source platform in the context of optical networks. Network elements and devices are implemented as IoT devices, and the control application is built on top of an OneM2M-compliant server. The work concretely addresses the scalability and flexibility performances of the proposed solution, accounting for the expected growth of optical networks. The two experiment scenarios show promising results and confirm that the OneM2M platform can be adopted in such a context, paving the way to other researches and studies.

The proliferation of Internet of Things (IoT) applications in safety-critical domains, such as healthcare, smart transportation, and industrial automation, demands robust solutions for data integrity, traceability, and security that surpass the capabilities of centralized databases. This paper analyzes how blockchain technology can be integrated with core IoT service functions—including data management, security, device management, group coordination, and automated billing—to enhance immutability, trust, and operational efficiency. Our analysis identifies practical use cases such as consensus-driven tamper-proof storage, role-based access control, firmware integrity verification, and automated micropayments. These use cases showcase blockchain’s potential beyond traditional data storage. Building on this, we propose a novel framework that integrates a permissioned distributed ledger with a standardized IoT service layer platform through a Blockchain Interworking Proxy Entity (BlockIPE). This proxy dynamically maps IoT service functions to smart contracts, enabling flexible data routing to conventional databases or blockchains based on the application requirements. We implement a Dockerized prototype that integrates a C-based oneM2M platform with an Ethereum-compatible permissioned ledger (implemented using Hyperledger Besu) via BlockIPE, incorporating security features such as role-based access control. For performance evaluation, we use Ganache to isolate proxy-level overhead and scalability. At the proxy level, the blockchain-integrated path achieves processing latencies (≈86 ms) comparable to, and slightly faster than, the traditional database path. Although the end-to-end latency is inherently governed by on-chain confirmation (≈0.586–1.086 s), the scalability remains high (up to 100,000 TPS). This validates that the architecture secures IoT ecosystems with manageable operational overhead.

High particulate matter (PM) concentrations in the cleanroom semiconductor factory have become a significant concern as they can damage electronic devices during the manufacturing process. PM can be predicted before becoming more concentrated based on its historical data to support factory management in regulating the air quality in the cleanroom. In this paper, a Multi-Dense Layer BiLSTM model is proposed to predict PM2.5 concentrations in the indoor environment of the cleanroom. To obtain reliability, validity, and interoperability data, the datasets containing temperature, humidity, PM0.3, PM0.5, PM1, PM2.5, PM5, and PM10 were retrieved in a standardized manner via oneM2M-defined representational state transfer application programmable interfaces by employing software platforms compliant with the Internet of Things (IoT) standard. Based on the proposed model, an algorithm was built providing short-term PM2.5 concentration predictions (one hour ahead, two hours ahead, and three hours ahead). The proposed model outperformed the RNN, LSTM, CNN-LSTM, and Single-Dense Layer BiLSTM models in terms of MSE, MAE, and MAPE values. The model created in this study could predict high PM2.5 concentration levels more accurately, thus providing vital support for operation and maintenance for the semiconductor industry.