Sensor Fusion Market

Global Sensor Fusion Market Size (2023 to 2028)

The global Sensor Fusion market size is expected to be worth 5.01 Billion USD in 2023. It is expected to grow at a CAGR of 17.36% during the forecast period and reach a value of 11.16 Billion USD by 2028.

Sensor fusion is the process of merging sensor data or data gathered from other sources to produce information with less uncertainty than would be achievable if these sources were used separately. For example, merging several data sources, such as video cameras and Wi-Fi localization signals, could potentially yield a more precise location estimate of an indoor object. In this example, the term uncertainty reduction might relate to the consequence of an emerging view, such as stereoscopic vision, or it can refer to the term more accurate, more complete, or more dependable.

A fusion process data sources do not need to come from identical sensors. Direct fusion, indirect fusion, and fusion of the outputs of the first two can all be distinguished. Direct fusion uses information sources such as a priori knowledge about the environment and human input to combine sensor data from a set of heterogeneous or homogeneous sensors, soft sensors, and sensor data history values, whereas indirect fusion uses information sources such as a priori knowledge about the environment and human input.

Global Sensor Fusion Market Drivers:

The actual growth of IoT technology, yet because of the development of autonomous or driverless vehicles, will bring new opportunities to the world market. Sensor fusion applications will be defined as a technology that mixes data from multiple sensors to form more accurate sensor images so as to boost advanced system performance or fix modern applications. Sensor fusion technology may be a sub-discipline of information fusion that's commonly brought up as multisensory data fusion or advanced sensor-data fusion. The thought of sensor fusion in automobiles is additionally gaining traction. Several research setups, current camera systems, and first image processing all use this notion focused. Differing types of sensor fusion are routinely utilized within the military for the goal of intelligent processing of remote sensing imagery. It contains built-in redundancy, which causes the system mechanism to transmit information whether or not there's a partial failure; as a result, it readily maintains its reliability and robustness. The world sensor fusion market study is extensive, with the goal of estimating market size and growth in the future.

Many new challenges within the field of image sensors are often overcome. For years, there has been plenty of predicted revenue generation in terms of rising volume in connection to the forthcoming market. The ever-growing demand for next-gen smartphones with advanced features and modern integrated sensors is assisting the sensor fusion market's growth.

Global Sensor Fusion Market Restraints:

The shortage of advanced qualified employees that leads to the efficient execution of various operations is one of the key issues that the industry faces on a worldwide scale. This multifaceted difficulty can be readily handled by holding multiple training sessions for a variety of unskilled employees. It has been demonstrated that there are numerous fast fixes for capturing the cost. A greater emphasis has been placed on the portfolio, resulting in excellent operational efficiency. The key disadvantages, such as time loss and risk, are the primary factors that compel businesses to implement solutions, as these elucidations provide detailed visuals and insights into the services.

REPORT COVERAGE:

This research report on the global sensor fusion market has been segmented and sub-segmented into the following categories.

Sensor Fusion Market- By Type:

• Radar Sensors.
• Image Sensors.
• IMU.
• Temperature Sensors.

IMU is expected to have the dominant share in the Global Sensor Fusion Market During the Forecast Period. The rising use of the GPS-IMU (Inertial Measurement Unit) fusion principle in ADAS is assisting in the resolution of accumulated dead reckoning errors in intervals with absolute position measurements. Tesla's Autopilot automatic driving feature is an example of an ADAS that can execute tasks such as establishing the vehicle's precise position from data obtained from a forward-facing camera and regulating the steering. ​

Sensor Fusion Market- By Technology:

• MEMS.
• Non-MEMS.

The MEMS Segment is expected to have the dominant share in the Global Sensor Fusion Market During the Forecast Period. An IMU can decrease to incredibly small sizes by utilizing MEMS technology. However, delivering good performance over a wide range of use cases, including significant temperature gradients common in applications such as automotive and avionics, can be difficult.

Sensor Fusion Market- By Industry Vertical:

• Automotive.
• Healthcare.
• Consumer Electronics.
• Aerospace & Defense.
• Industrial.

Automotive is expected to have the dominant share in the Global Sensor Fusion Market during the Forecast Period. Some of the most targeted applications in the examined industry are adaptive cruise control (ACC), autonomous emergency braking (AEB), and forward collision warning (FCW). BASELABS Gmbh, for example, launched BASELABS Create Embedded in June 2019, which works with Vector platforms to help speed up the development of embedded sensor fusion systems for automated driving functions and applications such as Adaptive Cruise Control (ACC), Automated Emergency Braking (AEB), Forward Collision Warning (FCW), and object fusion for piloted driving. Sensor fusion is now being used in heavy commercial vehicles as well as autonomous vehicles such as drones and industrial robots, thanks to the growing deployment of 5G technology. Due to expansion in businesses such as Mobility-as-a-Service (MaaS), smart buses, and robot taxis, 5G will dramatically bring Vehicle-to-everything (V2X) technology to the automotive and transportation industries, which will raise the need for sensor fusion. ​

Sensor Fusion Market- By Region:

• North America
• Europe
• Asia Pacific
• Latin America
• Middle East & Africa

Asia Pacific is expected to grow with a high CAGR in the Global Sensor Fusion Market During the Forecast Period. Due to the expanding acceptance of autonomous vehicles, severe government regulation, and increasing dominance in the global semiconductor industry, Asia Pacific is one of the most important locations for sensor fusion in autonomous applications. Furthermore, the region's significant investment in 5G, as well as its promotion of C-V2X, is broadening the breadth of automotive applications such as autonomous driving, V2X, and the MaaS market. Qualcomm is also collaborating with more than 30 Chinese automakers, including joint ventures based in China, to show the commercial viability of C-V2X technology for autonomous and connected vehicles. KT Corporation, based in South Korea, is developing a '5G as a Vehicle Platform,' a commercial self-driving platform based on the cutting-edge 5G technology.

KEY MARKET PLAYERS:

InvenSense, STMicroelectronics, NXP Semiconductors, Bosch Sensortec GmbH, Kionix, Analog Devices, Renesas Electronics Corp, Hillcrest Labs, Microchip technologies, Senion, Baselabs GmbH, Memsic

RECENT HAPPENINGS IN THE MARKET:

• Immervision and Halodi Robotics will collaborate to develop a vision system for humanoid robots. Halodi Robotics has chosen Immervision to supply its next-generation vision system for its humanoid service robot platform, which can handle both human and computer vision. Immervision is a developer of advanced vision systems combining optics, image processing, and sensor fusion technologies.
• Marelli, a prominent worldwide automotive supplier, has announced the addition of a new state-of-the-art Wireless Distributed Battery Management System to its range of battery management solutions for electric vehicles (WBMS). The Marelli wBMS can be equipped with a sophisticated software application layer that employs complex algorithms based on a patented 'Sensor Fusion' technology. The algorithms calculate various critical metrics of each battery cell, such as State of Charge, State of Health, and State of Power, to enable a more precise computation of the battery's overall status and to notify the powertrain's other components accordingly.