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An Overview of IoT Sensor Data Processing, Fusion, and Analysis Techniques.

Rajalakshmi Krishnamurthi1, Adarsh Kumar2, Dhanalekshmi Gopinathan1

  • 1Department of Computer Science and Engineering, Jaypee Institute of Information Technology, Noida 201309, India.

Sensors (Basel, Switzerland)
|October 29, 2020
PubMed
Summary

This paper overviews processing, fusion, and analysis of Internet of Things (IoT) sensor data. It addresses challenges like data quality and resource costs for better decision-making.

Keywords:
Internet of Thingsdata analysisdata fusiondata processingemerging technologies

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Area of Science:

  • Computer Science
  • Data Science
  • Internet of Things

Background:

  • The Internet of Things (IoT) enables solutions for smart cities, healthcare, and environmental monitoring.
  • Real-time IoT sensor data present challenges including data quality issues and high resource costs.
  • Effective data processing, fusion, and analysis are crucial for leveraging IoT data.

Purpose of the Study:

  • To provide a comprehensive overview of techniques for processing, fusing, and analyzing IoT sensor data.
  • To address the challenges associated with real-time IoT sensor data.
  • To explore the integration of IoT data analysis with emerging computing paradigms.

Main Methods:

  • Data processing techniques: denoising, outlier detection, missing data imputation, and aggregation.
  • Data fusion methods: direct fusion, associated feature extraction, and identity declaration.
  • Integration with cloud, fog, and edge computing for IoT sensor data analysis.

Main Results:

  • The paper details essential data processing steps to handle unclean sensor data.
  • It elaborates on various data fusion strategies to combine information from multiple sources.
  • The study discusses the integration of IoT data analysis with advanced computing infrastructures.

Conclusions:

  • This work presents a complete overview of IoT sensor data processing, fusion, and analysis techniques.
  • Addressing data quality and resource constraints is key for effective IoT applications.
  • Integrating IoT data analysis with cloud, fog, and edge computing offers solutions to current challenges.