Browsing by Author "Sandeep, M."

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    Data Format Heterogeneity in IoT-Based Ambient Assisted Living: A Survey
    (Springer Science and Business Media Deutschland GmbH, 2023) Sandeep, M.; Khatri, S.; Chandavarkar, B.R.
    Ambient Assisted Living (AAL) has become a significant component of the lives of the elderly in the present decade, allowing them to live independently by assisting their daily activities with automation. Different sensors from various manufacturers with proprietary data formats to detect environmental changes and monitor a person’s health metrics. These data formats are the root cause of the data Heterogeneity issue in AAL and, in turn, contribute to data interoperability challenges. In this paper, we have presented a survey on currently available state-of-the-art solutions to address data heterogeneity challenges in AAL and made a comparative study of suggested methods to overcome the data interoperability. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
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    Data Processing in IoT, Sensor to Cloud: Survey
    (Institute of Electrical and Electronics Engineers Inc., 2021) Sandeep, M.; Chandavarkar, B.R.
    IoT is connecting Things over the Internet and the realization of the environment through smart things to create a responsive space. Many surveys predicted the growth of IoT devices is going to be around 50 billion and an average of 7 devices per person. IoT has shown promising future with its applications like smart city, connected factories, buildings, roadways, smart health and many more. To make the promise a reality IoT has to overcome many hurdles like scalability, connectivity, architectural, big data, analysis, security, and privacy. In this literature survey, an attempt has been made to identify current challenges faced by IoT implementation and possible solutions, future opportunities, and research openings. Further, the processing of sensed data at IoT device, edge/fog layer, and the cloud is discussed in detail. © 2021 IEEE.
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    Integration of Synergetic IoT Applications with Heterogeneous Format Data for Interoperability Using IBM ACE
    (Springer, 2024) Sandeep, M.; Chandavarkar, B.R.
    Data interoperability is a crucial requirement in IoT to improve services and enhance business opportunities and innovation. Integrating synergetic applications with heterogeneous data formats is a critical issue that needs to be addressed to achieve interoperability. The use cases indicate IBM ACE is promising in resolving integration issues among on-premises and cloud applications. Further, many efforts are observed to address the interoperability issue apart from the IBM ACE approach. However, they are complex, restricted to few data formats, and use proprietary solutions. To address these above-mentioned issues, this paper proposes the Integration of Synergetic IoT applications with Heterogeneous format data for Interoperability using IBM ACE (ISHII). Further, an intelligence-based data recognition module in the proposed ISHII is trained with standard features defined in RFC 7111, 8259, 8996, JSON-LD of W3C, and Google’s Protobuf. Subsequently, recognized heterogeneous format data are integrated and translated to interoperable format using Data Format Description Language (DFDL) with Extended SQL codes on IBM ACE. Finally, the performance of ISHII has been evaluated with synthetically generated patient monitoring and room ambiance datasets with reference to accuracy, time required for integration, and translation efficiency. © 2023, The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd.
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    IoT's Communication Technologies, Data Formats, and Protocols-A survey
    (Institute of Electrical and Electronics Engineers Inc., 2021) Sandeep, M.; Chandavarkar, B.R.
    The efficient implementation of the Internet of Things (IoT) depends on the identification of the resources, representation of the measured values in a suitable format, efficient communication among resource-constrained things, and analysis adopted. In this paper different data formats, protocols, and new data specifications are explored. Protocols at different layers of IoT architectures are analyzed, compared and findings are represented. The study provides the user the knowledge to adopt technology to their need and implement IoT effectively. © 2021 IEEE.