MEMS-based thermoelectric infrared sensors： A review

In the past decade, micro-electromechanical systems （MEMS）-based thermoelectric infrared （IR） sensors have received considerable attention because of the advances in micromachining technology. This paper presents a review of MEMS-based thermoelectric IR sensors. The first part describes the physics of the device and discusses the figures of merit. The second part discusses the sensing materials, thermal isolation micro- structures, absorber designs, and packaging methods for these sensors and provides examples. Moreover, the status of sensor implementation technology is examined from a historical perspective by presenting findings from the early years to the most recent findings.

A Self‑Powered,Highly Embedded and Sensitive Tribo‑Label‑Sensor for the Fast and Stable Label Printer

Label-sensor is an essential component of the label printer which is becoming a most significant tool for the development of Internet of Things(IoT).However,some drawbacks of the traditional infrared label-sensor make the printer fail to realize the high-speed recognition of labels as well as stable printing.Herein,we propose a selfpowered and highly sensitive tribo-label-sensor(TLS)for accurate label identification,positioning and counting by embedding triboelectric nanogenerator into the indispensable roller structure of a label printer.The sensing mechanism,device parameters and deep comparison with infrared sensor are systematically studied both in theory and experiment.As the results,TLS delivers 6 times higher signal magnitude than traditional one.Moreover,TLS is immune to label jitter and temperature variation during fast printing and can also be used for transparent label directly and shows long-term robustness.This work may provide an alternative toolkit with outstanding advantages to improve current label printer and further promote the development of IoT.

Real-time optimization using gradient adaptive selection and classification from infrared sensors measurement for esterification oleic acid with glycerol

Purpose-The production of glycerol derivatives by the esterification process is subject to many constraints related to the yield of the production target and the lack of process efficiency.An accurate monitoring and controlling of the process can improve production yield and efficiency.The purpose of this paper is to propose a real-time optimization(RTO)using gradient adaptive selection and classification from infrared sensor measurement to cover various disturbances and uncertainties in the reactor.Design/methodology/approach-The integration of the esterification process optimization using self-optimization(SO)was developed with classification process was combined with necessary condition optimum(NCO)as gradient adaptive selection,supported with laboratory scaled medium wavelength infrared(mid-IR)sensors,and measured the proposed optimization system indicator in the batch process.Business Process Modeling and Notation(BPMN 2.0)was built to describe the tasks of SO workflow in collaboration with NCO as an abstraction for the conceptual phase.Next,Stateflow modeling was deployed to simulate the three states of gradient-based adaptive control combined with support vector machine(SVM)classification and Arduino microcontroller for implementation.Findings-This new method shows that the real-time optimization responsiveness of control increased product yield up to 13 percent,lower error measurement with percentage error 1.11 percent,reduced the process duration up to 22 minutes,with an effective range of stirrer rotation set between 300 and 400 rpm and final temperature between 200 and 210℃ which was more efficient,as it consumed less energy.Research limitations/implications-In this research the authors just have an experiment for the esterification process using glycerol,but as a development concept of RTO,it would be possible to apply for another chemical reaction or system.Practical implications-This research introduces new development of an RTO approach to optimal control and as such marks the starting point for more research of its properties.As the methodology is generic,it can be applied to different optimization problems for a batch system in chemical industries.Originality/value-The paper presented is original as it presents the first application of adaptive selection based on the gradient value of mid-IR sensor data,applied to the real-time determining control state by classification with the SVM algorithm for esterification process control to increase the efficiency.

Research Note: A Multi-Method Approach to Monitor Recreational Trail Usage in Complex Spatial Settings

Trail use by pedestrians has become more popular in the United States over the last decade although few studies explore the use of technology to monitor high use trails. Monitoring trail users is an important part of trail management and an optimal monitoring system usually depends on site-specific characteristics. The objective of this study was to demonstrate how using a multi-methods system to monitor backcountry trail usage in complex spatial settings can be a useful approach for collecting the information that trail managers need. Given the national growth in recreational hiking, we were particularly interested in exploring these issues for highly visited trails close to urban areas and selected a portion of the Larch Trail leading to the top of Multnomah Falls for the study. The multi-methods approach that we used included a combination of automated infrared sensor counts, manual counts, parking lot data from an inductive loop, and travel time estimates collected with low-energy Bluetooth sensors. We found that using multiple methods allowed for a cost-effective and rich data set that considered the site characteristics and the specific need of the trail managers. We expect that many backcountry trail settings have complex landscape and physical design without robust pre-existing baseline data and hope that our insights will aid trail managers as they strive for a sustainable balance between human use and landscape impact.

Camera calibration method for an infrared horizon sensor with a large field of view

Inadequate geometric accuracy of cameras is the main constraint to improving the precision of infrared horizon sensors with a large field of view(FOV).An enormous FOV with a blind area in the center greatly limits the accuracy and feasibility of traditional geometric calibration methods.A novel camera calibration method for infrared horizon sensors is presented and validated in this paper.Three infrared targets are used as control points.The camera is mounted on a rotary table.As the table rotates,these control points will be evenly distributed in the entire FOV.Compared with traditional methods that combine a collimator and a rotary table which cannot effectively cover a large FOV and require harsh experimental equipment,this method is easier to implement at a low cost.A corresponding three-step parameter estimation algorithm is proposed to avoid precisely measuring the positions of the camera and the control points.Experiments are implemented with 10 infrared horizon sensors to verify the effectiveness of the calibration method.The results show that the proposed method is highly stable,and that the calibration accuracy is at least 30%higher than those of existing methods.

A simple infrared nanosensor array based on carbon nanoparticles

A simple （2×2） pixelated flexible infrared nanosensor array based on carbon nanoparticles （CNPs） was fabricated through a simple and low-cost flame method. By integrated with a micro controller unit, the sensor array could detect power density of incident infrared light in real-time. The mechanism for the superior infrared sensing property of the flexible sensor array based on CNP was also studied in detail in this work.

Infrared Earth sensor with a large field of view for low-Earth-orbiting micro-satellites

Infrared Earth sensors are widely used in attitude-determination and control systems of satellites.The main deficiency of static infrared Earth sensors is the requirement of a small field of view(FOV).A typical FOV for a static infrared Earth sensor is about 20°to 30°,which may not be sufficient for low-Earth-orbiting microsatellites.A novel compact infrared Earth sensor with an FOV of nearly 180°is developed here.The Earth sensor comprises a panoramic annular lens(PAL)and an off-the-shelf camera with an uncooled complementary-metaloxide-semiconductor(CMOS)infrared sensor.PAL is used to augment FOV so as to obtain a complete infrared image of the Earth from low-Earth-orbit.An algorithm is developed to compensate for the distortion caused by PAL and to calculate the vector of the Earth.The new infrared Earth sensor is compact with low power consumption and high precision.Simulated images and on-orbit infrared images obtained via the micro-satellite ZDPS-2 are used to assess the performance of the new infrared Earth sensor.Experiments show that the accuracy of the Earth sensor is about 0.032°.

Synchronous line-tracking robots based on STM 32

A pair of synchronous line-tracking robots based on STM 32 are designed.Each robot is actually a small intelligent car with seven reflective infrared photoelectric sensors ST 188 installed in the front to track the line.Two rear wheels each driven by a moter are the driving wheels,while each moter is driven by an H-bridge circuit.The running direction is controlled by the turning of a servo fastened to the front wheel and the adjustment of speed difference between the rear wheels.Besides,the light-adaptive line-tracking can be performed.The speeds of the motors are controlled by adjusting pulse-width modulation(PWM)values and an angular displacement transducer is used to detect the relative position of the cars in real time.Thus,the speeds of the cars can be adjusted in time so that the synchronism of the cars can be achieved.Through experiments,the fast and accurate synchronous tracking can be well realized.

A Design of Remote-Controlled Chalkboard Eraser

Chalkboard erasers that are commonly used in many schools and education organizations have the poor ability in removing the dust off the chalkboard and collect them. The dust that is not collected will be taken into human bodies via inhalation, which will lead to respiratory diseases. Therefore, it is crucial to design a chalkboard eraser that can collect the dust effectively. If the eraser can be controlled both remotely and manually by people, it can further reduce the amount of dust taken in by human bodies. To achieve remote control, a micro-controller is needed to transfer the infrared radiation (IR) into signals that can control electric motors to move around on the chalkboard. Furthermore, the microfiber is also used as the cleaning material to improve the performance of dust cleaning and collecting. A vacuum pump is needed to create negative pressure between the eraser and the chalkboard so that the eraser can stick to it. The result shows a stronger ability in removing and collecting dust. With the help of the Arduino UNO board, the remote control is successfully achieved, and the eraser can move on the chalkboard freely according to the order.

Development and Evaluation of an Optical Sensing System for Detection of Herbicide Spray Droplets

Real time monitoring of herbicide spray droplet drift is important for crop production management and environmental protection. Existing spray droplet drift detection methods, such as water-sensitive paper and tracers of fluorescence and Rubidium chloride, are time-consuming and laborious, and the accuracies are not high in general. Also, the tracer methods indirectly quantify the spray deposition from the concentration of the tracer and may change the drift characteristics of the sprayed herbicides. In this study, a new optical sensor system was developed to directly detect the spray droplets without the need to add any tracer in the spray liquid. The system was prototyped using a single broadband programmable LED light source and a near infrared sensor containing 6 broadband spectral detectors at 610, 680, 730, 760, 810, and 860 nm to build a detection system for monitoring and analysis of herbicide spray droplet drift. A rotatory structure driven by a stepper motor in the system was created to shift the droplet capture line going under the optical sensor to measure and collect the spectral signals that reflect spray drift droplets along the line. The system prototype was tested for detection of small (Very Fine and Fine), medium (Medium), and large (Coarse) droplets within the droplet classifications of the American Society of Agricultural and Biological Engineers. Laboratory testing results indicated that the system could detect the droplets of different sizes and determine the droplet positions on the droplet capture line with 100% accuracy at the wavelength of 610 nm selected from the 6 bands to detect the droplets.