ReviewSensors (Basel, Switzerland)2020
An Overview of IoT Sensor Data Processing, Fusion, and Analysis Techniques.
Review in Sensors (Basel, Switzerland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
36 citing papers in PubMed, 373 citations in OpenAlex.
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- Development and validation of a sensor-integrated smart driving test system for automated, scalable, and objective driver performance evaluation.Scientific reports · 2026Article
- Proactive fault prediction in marine diesel engines using multivariate machine learning.Scientific reports · 2026Article
- IoT-LLM: A framework for enhancing large language model reasoning from real-world sensor data.Patterns (New York, N.Y.) · 2026Article
- Advances in IoT, AI, and Sensor-Based Technologies for Disease Treatment, Health Promotion, Successful Ageing, and Ageing Well.Sensors (Basel, Switzerland) · 2025Review
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- Examining the factor's influencing IoT-blockchain based secure transmission services.Scientific reports · 2025Article
- Multidomain Molecular Sensor Devices, Systems, and Algorithms for Improved Physiological Monitoring.Micromachines · 2025Review
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- Hybrid Mode Sensor Fusion for Accurate Robot Positioning.Sensors (Basel, Switzerland) · 2025Review
- Smart Dust for Chemical Mapping.Advanced materials (Deerfield Beach, Fla.) · 2025Review
- Artificial Intelligence and Internet of Things Integration in Pharmaceutical Manufacturing: A Smart Synergy.Pharmaceutics · 2025Review
- Enhancing safety in surface mine blasting operations with IoT based ground vibration monitoring and prediction system integrated with machine learning.Scientific reports · 2025Article
- Revolutionising health monitoring: IOT-Based system with machine learning classification.Health systems (Basingstoke, England) · 2025Article
- An advanced error state Kalman filter (ESKF)-based terrain contour matching (TERCOM) method for tracking an aerial vehicle using a low-cost digital elevation map.PeerJ. Computer science · 2025Article
- A Fusion Tracking Algorithm for Electro-Optical Theodolite Based on the Three-State Transition Model.Sensors (Basel, Switzerland) · 2024Article
- Indoor Infrared Sensor Layout Optimization for Elderly Monitoring Based on Fused Genetic Gray Wolf Optimization (FGGWO) Algorithm.Sensors (Basel, Switzerland) · 2024Article
- A Recommendation System for Prosumers Based on Large Language Models.Sensors (Basel, Switzerland) · 2024Article
- Revolutionizing elderly care: Building a healthier aging society through innovative long-term care systems and assessing the long-term care acceptance model.Geriatrics & gerontology international · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 4 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In the recent era of the Internet of Things, the dominant role of sensors and the Internet provides a solution to a wide variety of real-life problems. Such applications include smart city, smart healthcare systems, smart building, smart transport and smart environment. However, the real-time IoT sensor data include several challenges, such as a deluge of unclean sensor data and a high resource-consumption cost. As such, this paper addresses how to process IoT sensor data, fusion with other data sources, and analyses to produce knowledgeable insight into hidden data patterns for rapid decision-making. This paper addresses the data processing techniques such as data denoising, data outlier detection, missing data imputation and data aggregation. Further, it elaborates on the necessity of data fusion and various data fusion methods such as direct fusion, associated feature extraction, and identity declaration data fusion. This paper also aims to address data analysis integration with emerging technologies, such as cloud computing, fog computing and edge computing, towards various challenges in IoT sensor network and sensor data analysis. In summary, this paper is the first of its kind to present a complete overview of IoT sensor data processing, fusion and analysis techniques.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.