Overview
Sensor fusion and integration is the process of combining data from multiple sensors in order to improve accuracy and reliability of data. It is beneficial in a wide range of applications including navigation, robotics, surveillance, and safety-critical systems. Sensor fusion is used to combine inputs from a variety of types of sensors, including those that measure movement, sound, temperature, pressure, etc. This allows for more accurate results, as each different type of sensor may detect different details or provide more precise data. Additionally, sensor fusion reduces the number of false positives or anomalies from any given sensor. By combining the data from multiple sensors, any errors or inconsistencies can be eliminated, resulting in improved accuracy and reliability. Sensor fusion can be used in a wide variety of applications, such as tracking objects, monitoring people's movements, or providing input to robotic systems.
Research published in this journal
1 peer-reviewed article, ranked by relevance. Each links to its DOI.
How this research is being cited
The 1 article above has been cited 13 times in the scholarly literature. Citation data via OpenAlex and Crossref, updated Jun 2026.
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2026 · Journal of the Indian Society of Remote Sensing
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Grishma Ojha et al. · 2025 · European Journal of Applied Science, Engineering and Technology
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Sandeep Chataut et al. · 2025 · European Journal of Applied Science, Engineering and Technology
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2025 · Deleted Journal
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2025 · Journal of the Indian Society of Remote Sensing
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2025 · Deleted Journal
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Saurabh Chalise et al. · 2024 · European Journal of Theoretical and Applied Sciences
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Grishma Ojha et al. · 2024 · European Journal of Theoretical and Applied Sciences
A sample of recent works citing this journal's research on Sensor Fusion and Integration, linking to each citing work.