Multimodal sensors are advanced systems that integrate data from various types of detectors to collect extensive data about the environment or a specific situation. These detectors provide a more comprehensive and accurate image than any one detector could on its own, by integrating sensitive data from optical, auditory, tactile, olfactory, and other sources, compensating the failure modes of each sensor with abilities of another one.
Multimodal data and sensors have emerged as an important aspect of the IoT and AI concepts. Whether it is healthcare, education, media, transportation, environmental, or security monitoring, these sensors are doing a great job in deriving accurate and precise data for betterment of the society. It is majorly important in the development of autonomous vehicles and smart infrastructure.
It can cross-check data gathered from multiple sensors. This leads to a high accuracy rate and better assurance. Further detailed discussion below will give a better understanding of the multimodal sensors in both autonomous vehicles and smart infrastructure –
Autonomous Vehicles
1. Environment sensitive accurate data
Autonomous vehicles (AVs) require accurate data of the surroundings for a safe ride. Sensors like cameras, ultrasonic sensors, and LIDAR, all prepare a thorough map in a GPS tracker. For example, a camera provides visual data, while radar detects objects. During fog when headlights are of no use, then thermal imaging technology activates, thereby giving the driver a better understanding of the road, making their journey safe. The 3D smart sensing ability can detect pedestrians, obstacles, and other hurdles, thereby reducing the chances of accidents.
2. Good navigation
Unpredictable weather, dynamic road conditions, and different lighting conditions can always be a challenge during a road journey. For a safe drive, AVs rely on multimodal sensors like GPS, visual sensors, and inertial measurement units. For example, GPS provides a road map, but it can sometimes provide inaccurate data in bad signal areas. Therefore, the IMUs and visual sensors help in providing short-distance tracks and capture vehicle position and other objects in motion with changes in the environment. This combination of sensing technology can allow a vehicle to continuously move safely with validated data under challenging environments.
Advanced Smart Infrastructure
1. Integrated monitoring of society
Smart cities use multimodal sensors for a variety of reasons. For example, to check air quality, traffic conditions, and energy consumption, and predict urban environmental conditions. The integrated data from sensors like IoT devices, CCTV cameras, etc. help city planners to enhance urban living. For example, air quality and traffic sensors can identify the root cause of poor air quality. Therefore, they can make changes or divert routes to avoid traffic congestion and improve the air quality of that area. Other sensors used by industrialists help in building a better society by monitoring and minimizing waste disposal and allocating the right resources.
2. Better security and safety
Better living and society also include public safety. Advanced surveillance system helps in threat detection and better security. Integrated audio, video, 3D smart sensing, and motion sensors provide security solutions. The combination of multimodal sensors allows better detection of potential threats, suspicious activities, and quick deployment of emergency services.
Conclusion
Multimodal sensors are imperative for the development of AVs and smart infrastructure. However, the most important thing is buying it from a reliable brand. Choose the brand wisely after thorough research to keep your and your loved ones’ lives safe.
