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Early detection of forest fires offers the chance to put the fire out before it gets out of control. The purpose of this paper is to look into nature and to learn how certain insects detect remote forest fires. A small group of highly specialized insects that have been called pyrophilous is attracted by forest fires and approaches fires sometimes from distances of many kilometers. As a unique feature some of these insects are equipped with infrared (IR) receptors, which in case of two species of jewel beetles (family Buprestidae) are used for fire detection.

The paper has investigated the IR receptors of the pyrophilous beetles with various morphological techniques including scanning electron microscopy, transmission electron microscopy, neuroanatomy and the paper also investigated the thermo-/mechanical properties of the IR receptors by nanoindentation. Data were used for subsequent modeling of a biomimetic technical sensor. Finally, a macroscopic prototype was built and tested.

This biological principle was transferred into a new kind of uncooled technical IR receptor. A simple model for this biological IR sensor is a modified Golay sensor in which the gas has been replaced by a liquid. Here, the absorbed IR radiation results in a pressure increase of the liquid and the deflection of a thin membrane. For the evaluation of this model, analytical formulas are presented, which permits the calculation of the pressure increase in the cavity, the deformation of the membrane and the time constant of an artificial leak to compensate ambient temperature changes. Some organic liquids with high thermal expansion coefficients may improve the deflection of the membrane compared to water.

Results so far obtained suggest that it seems promising to take the photomechanic IR receptors of pyrophilous jewel beetles as models for the building of new uncooled IR sensors. The beetle receptors have been shaped by evolution since thousands of years and, therefore, can be considered as highly optimized sources of inspiration for new technical sensors suitable for remote fire detection.

This work encompasses the various laboratory-based and portable methods evolved in recent times for sensitive and selective detection of ethylene for fruit-ripening application. The role of ethylene in natural and artificial fruit ripening and the associated health hazards are well known. So there is a growing need for ethylene detection. This paper aims to highlight potential methods developed for ethylene detection by various researchers, including ours. Intense efforts by various researchers have been on since 2014 for societal benefits.

The paper focuses on types of sensors, fabrication methods and signal conditioning circuits for ethylene detection in ppm levels for various applications. The authors have already designed, developed a laboratory-based set-up belonging to the electrochemical and optical methods for detection of ethylene.

The authors have developed a carbon nanotube (CNT)-based chemical sensor whose performance is higher than the reported sensor in terms of material, sensitivity and response, the sensor element being multi-walled carbon nanotube (MWCNT) in comparison to single-walled carbon nanotube (SWCNT). Also the authors have developed infrared (IR)-based physical sensor for the first time based on the strong IR absorption of ethylene at 10.6 µm. These methods have been compared with literature based on comparable parameters. The review highlights the potential possibilities for development of portable device for field applications.

The authors have reported new chemical and physical sensors for ethylene detection and quantification. It is demonstrated that it could be used for fruit-ripening applications A comparison of reported methods and potential opportunities is discussed.

In this chapter, an attempt has been made to develop a security-based hardware system using an 8-bit single-chip microcontroller in conjunction with some sensor technology and lighting and alarming actuators. The proposed system aims to ensure the security and privacy of a dedicated area in terms of unauthorized human intrusion, hazardous gas leakage, extreme prolonged temperature changes, atypical smoke or vapor content in space and abrupt drop in illumination. The proposed system is capable of detecting any type of physical intervention and hazardous anomalies in the environment of the reserved space. In order to define the operation of the system, programs written in C++ with the special rule of code structuring have been deployed on the microcontroller using the Arduino Integrated Development Environment. The system is like a small container, enclosing all the respective sensor modules, microcontroller board and open connections for actuators. The proposed system is easy to use hardware and does not demand any human intervention for its functioning and can be installed with almost no changes in the infrastructure.

As real‐time, high‐fidelity visual scene simulation has become ubiquitous in the training, modeling and simulation community, a growing need for more than “out‐the‐window” scene simulation has developed. A strong requirement has developed for the ability to simulate the output of different types of sensors, especially electro‐optical (EO), infrared (IR), night vision goggle (NVG) and radar systems. To satisfy the need for advanced sensor simulation, Evans & Sutherland (E&S) has developed a physics‐based, dynamic, real‐time sensor simulation which allows users to model advanced EO, IR and NVG devices that are fully correlated with the “out‐the‐window” visual view. In this paper, the unique sensor simulation capabilities of E&S will be described. A brief description of the physics employed, input and output are presented along with example images.

Autonomous vehicles rely on IoT-based technologies to take numerous decisions in real-time situations. However, added information from the sensor readings will burden the system and cause the sensors to produce inaccurate readings. To overcome these issues, this paper aims to focus on communication between sensors and autonomous vehicles for better decision-making in real-time. The system has unique features to detect the upcoming and ongoing vehicles automatically without intervention of humans in the system. It also predicts the type of vehicle and intimates the driver.

The system is designed using the ATmega 328 P and ESP 8266 chip. Information from ultrasonic and infrared sensors are analyzed and updated in the cloud server. The user can access all these real-time data at any point of time. The stored information in cloud servers is used for integrating artificial intelligence into the system.

The real-time sensor information is used to predict the surrounding environment and the system responds to the user according to the situation.

The system is implemented on embedded platform with IoT technology. The sensor information is updated to the cloud using the Blynk application for the user in real time.

The system is proposed for smart cities with IoT technology where the user and the system are aware of the surrounding environment. The system is mainly concerned with the accuracy of sensors and the distance between the vehicles in real-time environment.

Data acquisition and data fusion of large numbers of sensors present unique challenges for control systems designers and applications engineers alike. In recent years the sensors industry has been moving towards the use of smart sensors, fieldbus networks, and localized smart processes. Merritt Systems Inc. of Rockledge, Florida, has been in the forefront of these developments since 1987 when it started pursuing the development of large sensor networks for robotic obstacle avoidance. As a result of this work a number of unique smart sensors and network technologies have been developed which have a wide range of applications beyond robotics. These include: one of industry’s first smart sensors, smart sensor networks, PC‐based data acquisition and control systems, and novel robotic modelling and motion planning algorithms. Whenever large networks of sensors with mixed sensing media are used, this technology has far‐reaching applications to industry and the research community.

The purpose of this research is to provide the necessarily and resourceful information regarding range sensors to select the best fit sensor for robust autonomous navigation. Autonomous navigation is an emerging segment in the field of mobile robot in which the mobile robot navigates in the environment with high level of autonomy by lacking human interactions. Sensor-based perception is a prevailing aspect in the autonomous navigation of mobile robot along with localization and path planning. Various range sensors are used to get the efficient perception of the environment, but selecting the best-fit sensor to solve the navigation problem is still a vital assignment.

Autonomous navigation relies on the sensory information of various sensors, and each sensor relies on various operational parameters/characteristic for the reliable functioning. A simple strategy shown in this proposed study to select the best-fit sensor based on various parameters such as environment, 2 D/3D navigation, accuracy, speed, environmental conditions, etc. for the reliable autonomous navigation of a mobile robot.

This paper provides a comparative analysis for the diverse range sensors used in mobile robotics with respect to various aspects such as accuracy, computational load, 2D/3D navigation, environmental conditions, etc. to opt the best-fit sensors for achieving robust navigation of autonomous mobile robot.

This paper provides a straightforward platform for the researchers to select the best range sensor for the diverse robotics application.

The purpose of this paper is to design and develop an IR and sprinkler based embedded controller operated robotic arm for automatic dust removal system to mitigate the dust effect on the solar panel surface, since dust accumulation normally affected by real weather conditions is one of the serious concern for the deterioration of photovoltaic (PV) system output.

The system is a wet cleaning device which provides a cheap silicon rubber-based wiping operation controlled by the pulse width modulation-operated motors of robotic arm. The IEEE 1149.1-compliant mixed signal-embedded platform of C8051F226DK is involved to command the complete system.

A prototype of 30 W_P system is capable of producing an inspiring average value of 11.26 per cent in energy increase, 13.63 per cent in PV module efficiency and 85.20 per cent in performance ratio of the system after 73 days of cleaning in summer season. In addition, a total of 1,617.93 W power; 1,0516.55 Wh energy; and 350.55 KWh/KW_P final yield was found during the entire cleaning period.

A novel technique of the implementation of IR sensor and sprinkler in dust mitigation is proposed in this paper. The IR sensor is used as a versatile object which can manage the robotic arm setting and control the automatic switching between cleaning and charging, as well as identify the thermal condition of solar panel for overheating.

The purpose of this paper is to provide an insight into China's burgeoning sensor industry.

Following an introduction to the Chinese economy and sensor market, this paper considers a number of key sensor applications and technologies and highlights a selection of Chinese sensor manufacturers and their products. It concludes with an overview of the country's sensor research effort.

This shows that China's sensor market is expanding very rapidly and is being served by a fast‐growing community of manufacturers who are producing large numbers of sensors for physical and chemical variables. The automotive sector is one of the leading users of sensors and is aiding China's micro‐electromechanical system industry. China has a large and active sensor research community.

This paper provides an up‐to‐date review of the Chinese sensor industry, illustrating its very rapid, recent growth and huge future potential.

Highlights the use of infrared and ultraviolet for flame detection, emission monitoring and thermal imaging. Describes the application of an infrared fire detection system at Courtaulds Chemicals and the use of thermal imaging for preventive maintenance at Blue Circle Cement.