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Object motion can be tracked using techniques, including ultrasonic waves, infrared waves, and microwaves. In this article, the applications of infrared motion sensors are discussed.

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The use of motion sensors has grown as their demand in domestic, manufacturing, robotics and medical industry rises.

An infrared sensor, which may be used in a variety of devices, is the most popular kind of motion detector. This sensor collects information regarding movement, which the device may utilize to notify the user when something is moving about or to take specific actions on their behalf.

Burglar alarms, for example, have motion detectors connected to them that may be activated when motion is detected. Similarly, these sensors are used in manufacturing industries and robotics to detect the motion and eventually act according to requirements.

Healthful aging is one of the most promising study subjects in several fields, including public health care, senior security systems, and biomedical engineering, due to the aging of the general population.

By limiting health care financing and developing biomedical engineering, these forces fuel the shift from institutionalized health care to home-based assisted living.

Home-based assisted living utilizes activity monitoring, and acknowledgment, helping to encourage healthy aging at home. This requires tracking and identifying a person's activities of daily living.

An article published in IEEE Sensors Journal presents an Infrared radiation change (IRC) based compressive classification approach for identifying the physical activities of interest in home-based assisted living.

IRC motion sensor modules are placed on the ceiling and on two tripods facing each other to catch the IRC in its entirety. The usefulness of this approach is shown in a pilot study, including categorizing six common physical activities using classification methods such as the hidden Markov model and support vector machine.

Several types of robots for automation and navigation have been designed in the last several years, including robots that follow walls and edges, avoiding obstacles as they move. When attempting to reach its intended destination, the obstacle-avoiding robot will avoid any impediments that stand in its way.

Due to their dependability, accessibility, and affordability, mobile robots for industrial and technical applications such as obstacle avoidance are critical on the manufacturing floor. As an alternative to this scenario, unmanned aerial vehicles (UAVs) serve a critical defense and civilian function.

Battle damage assessment and communications are also used in military applications. Meanwhile, disaster management, remote sensing, traffic monitoring, and so forth are examples of civilian uses.

Many UAV applications need the capacity to navigate through densely populated metropolitan areas or unfamiliar terrains filled with various obstacles of varying heights and widths. Detecting and avoiding obstacles is a fundamental prerequisite for autonomous UAVs.

Researchers published an article in IOP Science that uses infrared and passive infrared (PIR) sensors to demonstrate an obstacle avoidance robot algorithm.

Wireless sensor networks for home, workplace, or industrial security systems must be able to accurately track intruders; passive infrared motion sensors (PIR sensors) are excellent for these systems.

In an article published in IEEE, researchers discuss the performance and usefulness of PIR sensors for security systems. They present a person tracking algorithm based on the region presented, along with its actual implementation and trials in a real scenario.

This research proposes a surveillance tracking system based on PIR sensors that may be implemented utilizing wireless sensor network technologies. Evaluation of PIR sensors for surveillance and the influence of placement on algorithm performance were examined.

Infrared motion sensors are being widely used in the medical. Research published in Journal of Clinical Monitoring and Computing presents a novel concept that uses passive infrared (PIR) technology for contactless detection of breathing movement.

The research aimed to determine whether breathe motion detection system (BMDS) sleep movements were connected to breathing. In a second phase, this medical equipment identified central pathological apnea in adults. One hundred sixty-nine adult patients received complete polysomnography with BMDS.

The idea is simple, cost-effective, and safe for the patient to implement. RIP investigations are required to further examine BMDS's capability for detecting centralized apneas.

Infrared motion sensors are being used in wearable devices such as bands and smartwatches to track heart rate, steps, and oxygen levels to aid personal health monitoring.

Infrared motion sensors are being actively used in intruder alarms to keep the house safe from intruders. They are also used in hand dryers, automatic doors, automated sinks, toilet flushers and kitchens.

Despite the significant progress made in this field, more research is needed to improve the accuracy of IR motion sensors. The applications where these sensors often involve the user's safety, emphasizing the need for high-performance, accurate systems.

Ansari, R. et al. (2021) ‘Motion-based Thermal Sensing for Health Care Monitoring Systems ( HMS ) and Healthcare Applications’. Available at: doi.org/10.25417/uic.15261858.v1. 

Byunghun, S., Haksoo, C. and Hyung, SL (2008) ‘Surveillance tracking system using passive infrared motion sensors in wireless sensor network’, 2008 International Conference on Information Networking, ICOIN [Preprint]. Available at: doi.org/10.1109/ICOIN.2008.4472790.

Guan, Q. et al. (2016) ‘A novel infrared motion sensing system for compressive classification of physical activity’, IEEE Sensors Journal, 16(8), pp. 2251–2259. Available at: doi.org/10.1109/JSEN.2016.2514606.

Hers, V. et al. (2013) ‘New concept using Passive Infrared (PIR) technology for a contactless detection of breathing movement: A pilot study involving a cohort of 169 adult patients’, Journal of Clinical Monitoring and Computing, 27(5), pp. 521–529. Available at: doi.org/10.1007/s10877-013-9457-2.

Ismail, R., Omar, Z. and Suaibun, S. (2016) ‘Obstacle-avoiding robot with IR and PIR motion sensors’, IOP Conference Series: Materials Science and Engineering, 152(1). Available at: doi.org/10.1088/1757-899X/152/1/012064.

Yang, Y.H. et al. (2014) ‘The application of KINECT motion sensing technology in game-oriented study’, International Journal of Emerging Technologies in Learning, 9(2), pp. 59–63. Available at: doi.org/10.3991/ijet.v9i2.3282.

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Adeel is an aerospace engineer and a robotics enthusiast. He has been providing services related to aerospace on Upwork and Fiverr for more than 2 years. Being passionate about control engineering, machine learning and AI, he wants to pursue his career in these fields. He loves to travel around the world and make new friends worldwide. He has just started his research journey and will soon publish research papers related to control engineering, robotics and AI.

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