Sensor fusion involves the integration of sensory data or data obtained from sensory sources to produce information that is more valuable than what could be achieved by using these sources separately. Sensor fusion overcomes various problems that emanate from relying on a single sensor as a source of information such as deprivation due to breaking down of one of the sensors, lack of spatial or temporal coverage and imprecision.
Sensor fusion devices can be bifurcated into micro-elctro-mechanical systems (MEMS) and non-MEMS devices. MEMS sensors are the ones that use micro-scale technology to sense and then measure physical attributes like pressure, temperature, acceleration, and motion. These sensors are fitted on a silicon chip via microfabrication methods. Some of the common MEMS sensors include accelerometers, gyroscopes, pressure sensors, temperature sensors, microphones and others. Non-MEMS sensors don’t use microfabrication techniques for creating their sensing elements. They instead rely on other physical principles like light, magnetism, sound and others. Non-MEMS sensors can either be active or passive. Some of the common non-MEMS sensors include optical sensors, magnetic sensors, ultrasonic sensors, and radiation sensors.
Non-MEMS sensors provide better accuracy than MEMS ones, making them suitable for industrial processes, while, the MEMS sensors are smaller and more energy efficient. Hence, MEMS sensors are extensively used in wearable devices and smartphones.
In recent years sensor fusion has risen to prominent use in the automotive industry for a variety of purposes. Modern automobiles are equipped with a host of sensors such as cameras, radar, global positioning system (GPS) and others. Fusion of the data coming from each of these sensors gives a more all-encompassing overview of the environment around the automotive for the person operating it.
Advanced drives assistance systems (ADAS) is another one of the applications of sensor fusion where sensors are used to detect potential hazards and obstacles on the road. The same concept is used in autonomous driving, optimizing driving behavior and reducing the consumption of fuel. According to an article posted by Sasken Technologies in April 2020, Tesla uses radars and cameras with a neural network in their autonomous cars, on the other hand, the company Waymo, which is a subsidiary of Alphabet Inc. uses light detection and ranging (LIDAR) sensors in their automobiles.
The healthcare industry uses sensor fusion system in medical imaging operations like computed tomography (CT) scans, magnetic resonance imaging (MRI), positron emission tomography (PET) and others for detailed images. The defence sector also use sensor fusion technology for battlefield awareness purposes and unmanned aerial vehicles.
Inertial Measurement Unit (IMU)
By End User
Military & Defense
Analog Devices Inc.
Asahi Kasei Microdevices
Renesas Electronics Corporation
Bosch Sensortec GmbH
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