- Published on October 2, 2021
- In AI Features
Can AI Transform The Global Sensor Fusion Industry?
Due to the abundance of sensor data, sensor fusion is in high demand. AI-enabled sensor fusion has a wide range of applications.
- By Dr. Nivash Jeevanandam
Sensor fusion (SF) is in high demand due to the availability of sensor data from a variety of sources. Due to the inherent advantages and disadvantages of various sensor types, a good algorithm will also prioritise certain data points over others. SF techniques combine sensory input to assist in reducing ambiguity in machine perception when appropriately synthesised. They are tasked with the responsibility of integrating data from many sensors. Bayesian methods like Kalman Filters are frequently used to perform the fusion. There are a few more algorithms that are employed in the fusion process.
Existing Sensor Fusion Algorithms
SF algorithms combine all inputs and generate accurate and dependable output, even when individual measurements are incorrect. Let's have a look at some of th
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Dr. Nivash Jeevanandam
Nivash holds a doctorate in information technology and has been a research associate at a university and a development engineer in the IT industry. Data science and machine learning excite him.
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