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The Internet of Things (IoT) connects physical objects through networks, enabling autonomous operation and real-time data exchange across sectors such as healthcare, agriculture, smart cities, and industrial automation. As a rapidly evolving Complex Adaptive System, IoT faces major challenges in security, interoperability, data processing, and scalability. This literature survey systematically reviews the challenges and evaluates their proposed solutions such as Artificial Intelligence-based (AI-based) anomaly detection, predictive analytics, blockchain technologies, and Big Data frameworks like Hadoop, Spark, and Kafka. The paper also highlights standardized communication protocols and network optimization techniques in improving system efficiency. To illustrate strengths and limitations, reviewed techniques and methods are comparatively analysed and presented via graphical charts. In spite of advanced solutions, existing IoT architectures are required to be more secure, scalable and energy-efficient as some technical gaps still remain. Future work must focus on enhancing real-time data processing, ensuring scalability, and developing sustainable designs to support the widespread and reliable deployment of next-generation IoT systems.

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Bridging Gaps in IoT Literature: A Thematic Categorization of Challenges and Resolutions

  • 会议论文

  • 发表日期：

    2026年

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  • Twinkle Verma,
  • Muskan Rajak,
  • Nancy Kaim,
  • Nandini Sharma,
  • Nisha,
  • Harendra Pratap Singh

摘要

The Internet of Things (IoT) connects physical objects through networks, enabling autonomous operation and real-time data exchange across sectors such as healthcare, agriculture, smart cities, and industrial automation. As a rapidly evolving Complex Adaptive System, IoT faces major challenges in security, interoperability, data processing, and scalability. This literature survey systematically reviews the challenges and evaluates their proposed solutions such as Artificial Intelligence-based (AI-based) anomaly detection, predictive analytics, blockchain technologies, and Big Data frameworks like Hadoop, Spark, and Kafka. The paper also highlights standardized communication protocols and network optimization techniques in improving system efficiency. To illustrate strengths and limitations, reviewed techniques and methods are comparatively analysed and presented via graphical charts. In spite of advanced solutions, existing IoT architectures are required to be more secure, scalable and energy-efficient as some technical gaps still remain. Future work must focus on enhancing real-time data processing, ensuring scalability, and developing sustainable designs to support the widespread and reliable deployment of next-generation IoT systems.