Proximity Sensors Research Articles

Global Positioning System (GPS) pada Kotak Penyimpanan Uang Berbasis Internet Of Things

In this research, a money storage box security system will be designed. The box designed is a box equipped with a vibration sensor and a GPS module, where vibrations due to lifting or if someone carries it triggers an alarm in the form of a buzzer that sounds and the control system is based on the NodeMCU ESP8266 which immediately sends a warning message and also a Google Maps link to the application. The most competitive Telegram is paid for by smartphone so it can be taken quickly to prevent it. Create a secure storage box based on Arduino Uno and Telegram and design a security system to find the location of the box via GPS with notification media via Telegram. The hardware used is an ultraisonic sensor to measure the height of the box from the floor, an IR Proximity sensor as an object detector, a fingerprint to open the box, a buzzer as an alarm, a solenoid lock to lock the box, GPS as a guide if the box is stolen, and an ESP8266 NodeMCU as an input process and output. By utilizing wifi from the NodeMCU ESP8266 as a link between the device and the cellphone.

An Embedded System Approach to Design and Development of an Automatic Spin Coating Machine for Thin Film Applications

A typical spin coating technique entails three steps: dispense, in which the resin fluid is applied to the substrate surface; high-speed spin, in which the fluid is thinned; and drying, in which extra solvents are removed from the resultant film. For the growth of thin films, an embedded system-based spin coating machine has been developed. The PIC microcontroller (PIC16f877A), which might be powered by a driver circuit to drive a spinning motor, controls the spin coating machine effectively. The temperature sensor is used to determine the temperature, while the proximity sensor is used to determine the motor's speed. Using a temperature sensor, the temperature has been kept between 30 and 40 degrees Celsius. The developed system will coat thin films in a micro level thickness by adjusting the spinning speed and controlling the system using PIC microcontroller. To test the reliability and repeatability of the machine, Zinc oxide (ZnO) was prepared with the sol-gel technique and deposited on the glass substrate using embedded system based spin coating machine. ZnO thin films were prepared at different pH and exhibited the fundamental reflections of (100), (002), (101), and (102) with the hexagonal wurtzite crystal structure. The structural studies of ZnO thin films using XRD analysis confirm the presence of ZnO particles in the prepared films. Also, it ensures the prepared ZnO thin film is pure and that no other impurities have been observed in the XRD pattern.

The KIR2DL1 intermediate upstream element participates in gene activation

The human KIR genes encode a family of class I MHC receptors that are expressed on subsets of NK cells. The expression of KIR proteins is controlled by a stochastic process, and competition between sense and antisense promoter elements has been suggested to program the variegated expression of these genes. Previous studies have demonstrated distinct roles of distal, intermediate, and proximal sense promoter/enhancer elements in gene activation and expression. Conversely, proximal and intronic antisense promoter transcripts have been associated with gene silencing at different stages of NK cell development. In the current study, we examine the effect of intermediate promoter deletion on KIR2DL1 expression in the YTS cell line. Homozygous deletion of the KIR2DL1 intermediate element did not affect proximal promoter activity but resulted in increased detection of upstream transcripts. No significant changes in alternative mRNA splicing or expression levels of KIR2DL1 protein were observed. However, intermediate element deletion was associated with a reduced frequency of gene activation by 5-azacytidine. Taken together, these results indicate that the intermediate element is not an enhancer required for KIR expression; however, it is required for the efficient activation of the gene.

Comparing the predictive ability of Sentinel-2 multispectral imagery and a proximal hyperspectral sensor for the estimation of pasture nutritive characteristics in an intensive rotational grazing system

Using remote sensing to estimate the nutritive characteristics of pasture in livestock systems is a rapidly developing area that has the potential to improve pasture management and utilisation and in turn improve livestock productivity. The Copernicus Sentinel-2 paired satellites have shown promise in predicting pasture nutritive characteristics and have a pixel size small enough to be able to identify intra-paddock nutrient variation in rotational dairy grazing systems where paddock sizes are small. This study sought to develop nutrient prediction models using a dataset of nine Sentinel-2A and -2B satellite images, by linking imagery to perennial ryegrass dairy pasture samples cut within known pixels of the images in the days directly after each cloud-free overpass. Just before destructive pasture sampling, a handheld, proximal, hyperspectral sensor was used to gather spectral signatures (400–2500 nm) from areas to be sampled. Pasture samples (n = 200) were analysed using wet chemistry techniques for seven nutritive characteristics. The dry matter concentration of the samples was also measured, creating eight variates to be modelled in total. The Sentinel-2 data from within the selected pixels was extracted and used to create input features for Random Forest prediction models. Input features included the raw multispectral bands, common vegetation indices, and independent variables ‘season’ and ‘month’. Predictive models were also developed from the hyperspectral sensor data using Partial Least Squares Regression. For both modelling types, variable selection was used to reduce model inputs to only those sensitive to each nutrient. Results comparing the final models in an independent validation test showed similar predictive performance of the Sentinel-2 satellite and the proximal hyperspectral sensor for all variates of interest, shown by mean absolute errors that were not significantly different. In each case, the dry matter concentration was the best predicted variable (Lin’s concordance correlation coefficient (LCCC) > 0.90) with excellent potential to be quantified by Sentinel-2 satellites. Crude protein, metabolisable energy, neutral detergent fibre, non-fibre carbohydrate, and water-soluble carbohydrate concentrations were also predicted with good to moderate accuracy by both sensors (LCCC between 0.50 and 0.80). These models would be sufficiently accurate for making qualitative predictions (e.g., grouping into high to low categories). Ash and acid detergent fibre concentrations were poorly predicted (LCCC < 0.50) and these models would not be recommended for further use. It was concluded that multispectral data from Sentinel-2 has great potential to estimate pasture nutrient concentrations for intensively grazed pastures such as those used in dairy systems in temperate regions.

Research progress of multifunctional flexible proximity sensors

As a non-contact sensor, flexible proximity sensor can sense the proximity of target objects to achieve position recognition, obstacle avoidance, human-computer interaction and other functions. It has important application prospects in environmental detection, human health monitoring, robot electronic skin and other fields. In recent decades, a variety of flexible multifunctional sensors based on proximity sensing have emerged, and how to improve and optimize their performance has become a research hotspot. This review summarizes the classification, performance index and research progress of flexible proximity sensors with different sensing types. In particular, the design principle, structure composition, material selection and manufacturing process of the current flexible proximity sensors are discussed in detail. Then, the performance of proximity sensing, realizable functions and application scenarios are compared among the reviewed research results. Finally, we discuss the challenges faced by flexible proximity sensors, and summarize and prospect the research direction of flexible proximity sensors. This paper aims to provide important reference value for further improving and optimizing the performance of the flexible proximity sensor and developing the next generation of multifunctional wearable devices.

Unlocking the Performance of Proximity Sensors by Utilizing Transient Histograms

Unlocking the Performance of Proximity Sensors by Utilizing Transient Histograms

Railway Waste Management

Abstract: A smart waste management system is of great necessity looking at the current increase in waste produced every year. This is a very unorganized sector where no such precautions are taken for proper waste disposal. Railways face difficulty in managing the waste produced inside the coaches. In order to help the government and protect nature from corrosive nonbiodegradable waste this waste management system was designed. In this project Arduino UNO was the main processor used along with sensors like inductive proximity sensor and soil moisture sensor. The main principle of the project was based on the information processed by the sensors and effective segregation of the waste individual bins to store the waste produced. A main support is placed which helps in holding the complete structure together

Design Product Counting and Sorting Tools Using Esp8266-Based Volumenization

Indonesia is a large country, so it does not rule out the possibility of natural resources owned by Indonesia such as natural resources coal, petroleum, gas, nickel and many others When we enter the industrial world, especially placed in the production process area, more precisely the process of sorting goods, it is very necessary to optimize the performance and results of the effectiveness of these working hours so as to get high performance efficiency and will get maximum yield. In the shipping section there are several occurrences of problems which include three main activities of the process of receiving, storing and sending when receiving or sending. We recommend reducing errors at the time of delivery of goods. As for the problem of empty packaging and calculating the number of inappropriate products, by providing solutions using loadcell sensors for weight, proximity sensors for automatic counters and using google sheets as data storage in real time using esp8266 as a controller module.causing performance effectiveness that is expected to be better automatically and using the sophistication of IoT systems connected to the web system.and supported by several Components include relays, pneumatics, googlesheets in order to get accurate results, product sorting tools using this loadcell will be compared with loadcell weighing devices that have been on the market in order to find out how accurately it has obtained the appropriate results using a volume of 103gr. The results of the entire test tool get accurate data ranging from googlesheet to reading through Lcd 20x4 testing is carried out five times so that this tool can be applied to other supporting tools.that the entire tool is able to answer the problems of the developing industrial world.

Implementation of Behavior Based Robotics on Hexapod Legged Robot Based on Room Mapping

The Indonesian Fire Fighting Robot Contest (KRPAI) has a mission to extinguish fires quickly, with various kinds of points and bonuses to be taken. The robot used in this research is a 6-legged robot (Hexapod). The problem faced today is the robot's ability to navigate the room, the robot still has to enter the same room, especially in room 1 (a room with 2 doors) so that the Arbitrary Start bonus or Variable Door location which prohibits the robot from entering the same room cannot be obtained. There is also a Room Factor bonus obtained using the JTS (Segment Distance) method which is an additional bonus when the robot walks outside the room. It is necessary to develop a room mapping algorithm with behavior based so that the robot can get maximum points. The main sensor used is the IMU BNO055 sensor as a robot direction orientation sensor, as well as a proximity sensor as a wall search sensor, so that the robot can know the direction when leaving and exploring the room, knowing the starting room, and ensuring the next room entered is a different room. The results of the test successfully made the robot take maximum points in the race.

Can Yield Prediction Be Fully Digitilized? A Systematic Review

Going beyond previous work, this paper presents a systematic literature review that explores the deployment of satellites, drones, and ground-based sensors for yield prediction in agriculture. It covers multiple aspects of the topic, including crop types, key sensor platforms, data analysis techniques, and performance in estimating yield. To this end, datasets from Scopus and Web of Science were analyzed, resulting in the full review of 269 out of 1429 retrieved publications. Our study revealed that China (93 articles, &gt;1800 citations) and the USA (58 articles, &gt;1600 citations) are prominent contributors in this field; while satellites were the primary remote sensing platform (62%), followed by airborne (30%) and proximal sensors (27%). Additionally, statistical methods were used in 157 articles, and model-based approaches were utilized in 60 articles, while machine learning and deep learning were employed in 142 articles and 62 articles, respectively. When comparing methods, machine learning and deep learning methods exhibited high accuracy in crop yield prediction, while other techniques also demonstrated success, contingent on the specific crop platform and method employed. The findings of this study serve as a comprehensive roadmap for researchers and farmers, enabling them to make data-driven decisions and optimize agricultural practices, paving the way towards a fully digitized yield prediction.

Machine learning-based draft prediction for mouldboard ploughing in sandy clay loam soil

Machine learning (ML) models are developed to predict draft for mouldboard ploughs operating in sandy-clay-loam soil. The draft of tillage tools is influenced by soil cone-index, tillage-depth, and operating-speed. We used a three-point hitch dynamometer to measure draft force, a cone penetrometer for soil cone-index, rotary potentiometers for tillage-depth, and proximity sensors for operating-speed. Draft requirements were experimentally measured for a two-bottom mouldboard plough at three different tillage-depths and various operating-speeds. We developed prediction models using recent ML algorithms, including Linear-Regression, Ridge-Regression, Support-Vector-Machines, Decision-Trees, k-Nearest-Neighbours, Random-Forests, Adaptive-Boosting, Gradient-Boosting-Regression, Light-Gradient-Boosting-Machine, and Categorical-Boosting. These models were trained and tested using a dataset of field measurements including soil cone-index, tillage-depth, operating-speed, and corresponding draft values. We compared the measured draft with the commonly used ASABE model, which resulted in an R2 of 0.62. Our ML models outperformed the ASABE model with significantly better performance. The test data set achieved R2 values ranging from 0.906 to 0.983. These results demonstrate that the developed ML models effectively capture the complex nonlinear relationship between input parameters and draft of mouldboard plough.

Handwriting Character Recognition Based on Conductor/Insulator‐Identifiable E‐Tattoo Proximity Sensors for Blinds

AbstractEasy and convenient reading for blinds is of great significance for lowering their learning, entertainment, and communication barrier, and improving their living quality. The general solution is to learn braille, far from satisfying the meet of the blinds’ daily learning and communication. Here, a new‐type conductor/insulator‐identifiable e‐tattoo proximity sensor is developed by simply depositing the circular interdigitated electrodes on organic semiconductor. The discriminable recognition toward conductors and insulators is realized only based on a single e‐tattoo device. The sensors not only enable recognition of the protruding characters like braille based on distance difference, but also enable recognition of the handwriting ink‐brush and pencil graphite characters based on the unique advantage of the sensors in distinguishing conduct and insulator. These results open a new route to realize the material category recognition, provide a user‐friendly way to help the visual impaired effectively reintegrate into society, and broaden the application field of proximity sensors.

A parallel ring-ring capacitive proximity sensor for detection of approaching conductor

PurposeTo solve the problem of low sensitivity of traditional capacitive proximity sensor, this paper aims to propose a novel capacitive sensor for detection of an approaching conductor.Design/methodology/approachFive capacitive proximity sensors with different structures are designed and the performance is compared with the traditional capacitive sensor. The impacts of geometrical parameters on the performance of the proposed capacitive sensor are studied. Furthermore, the sensitivity of the proposed capacitive sensor to an approaching conductor with different sizes is discussed. Also, how the designed capacitive sensor is sensitive to the lateral placement of the approaching object is analyzed.FindingsSeveral capacitive proximity sensor structures have been designed and analyzed. It is found that the capacitive sensor with the top small ring-bottom large ring structure shows stronger electric field distribution around the top electrode and higher sensitivity to the approaching conductor than other sensors. Through further analysis of the proposed sensor, the results demonstrate that proposed capacitive sensor is effective for proximity object detection.Originality/valueThis paper proposes a novel capacitive proximity sensor with top small ring-bottom large ring structure. Compared with the traditional capacitive sensor, the proposed capacitive sensor is more sensitive to the approaching object. This would be helpful for the accurate detection of the approaching object. Also, the top and bottom electrodes are much smaller.

A smartphone-regulated system for facilitating access to music and telephone calls and providing timely activity instructions to people with intellectual and multiple disabilities

Background: People with intellectual and multiple disabilities often fail to achieve constructive occupation independent of external supervision. Technology-aided intervention systems might be used as a way to help them achieve such a goal. Method: A new technology-aided system was assessed with four participants with moderate to severe intellectual disability and blindness or blindness and motor impairment. The system (a) allowed the participants to access music events and telephone calls through simple responses, and (b) provided the participants with timely activity step instructions (i.e. instructions tied to their response performance). The system was based on the use of a smartphone linked to a proximity sensor and was introduced according to a non-concurrent multiple baseline across participants design. Results: During baseline, the participants were not able to independently access music and telephone calls or perform activities. During the intervention sessions, they managed all three forms of occupation independently (i.e. with the technology system), remaining constructively active throughout the sessions. Their mean occupation time per session was 18-28 min and their percentage of correct activity steps was higher than 95. Conclusions: The new technology-aided system might be useful for helping people with intellectual and other disabilities manage basic forms of constructive occupation.

Orange Dye and Silicone Glue Composite Gel-Based Optimized Impedimetric and Capacitive Surface-Type Proximity Sensors.

Optimized surface-type impedimetric and capacitive proximity sensors have been fabricated on paper substrates by using rubbing-in technology. The orange dye (OD) and silicone glue (SG) composite-gel films were deposited on the zig-zag gap between two aluminum electrodes fixed on a paper (dielectric) substrate. The effect of proximity of various objects (receivers) on the impedance and the capacitance of the sensors was investigated. These objects were semi-cylindrical aluminum (metallic) foil, a cylindrical plastic tube filled with water, a kopeck-shaped plastic tube filled with carbon nanotubes and a human finger. The mechanism of sensing was based on the change in impedance and/or the capacitance of the sensors with variation of proximity between the surfaces of the sensor and the object. On decreasing proximity, the impedance of the sensors increased while the capacitance decreased. The impedimetric proximity sensitivities of CNT, water, metal-based receivers and the finger were up to 60 × 103 Ω/mm, 35 × 103 Ω/mm, 44 × 103 Ω/mm and 6.2 × 103 Ω/mm, respectively, while their capacitive sensitivities were -19.0 × 10-2 pF/mm, -16.0 × 10-2 pF/mm, -16.4 × 10-2 pF/mm and -1.8 × 10-2 pF/mm. If needed for practical application, the sensors can be built in to the Wheatstone bridge, which can also increase the sensitivity of the measurement. Moreover, the sensor's materials are low cost, while the fabrication technique is easy and ecologically friendly. The sensor can also be used for demonstrative purposes in school and college laboratories.

Numerical Analysis of Inductive Proximity Sensors for Non-Ferrous Targets

Abstract Proximity sensors are devices found in many fields of activity from the automotive area to robotics and beyond. Among them, proximity sensors occupy an important place due to their low price and reliable response. They are found in a wide range of sizes and detection distances. In this work, a comparative study was carried out on two constructive solutions - one shielded and one unshielded. The response provided by the sensor was followed through a 2D FEMM analysis varying a series of parameters: the material from which the target is made, the distance between the target and the sensor, as well as its operating frequency. The results highlight the influence of these parameters by changing some quantities of a magnetic nature such as the spectrum of the magnetic flux density, the magnetic energy stored by the target, respectively the inductance of the sensor coil.

Actively shielded capacitive proximity sensor for endoscopy

Abstract Flexible endoscopes are widely used for diagnostic and therapeutic procedures on internal organs and tissue surfaces. Accurate positioning of the endoscope tip is critical for obtaining clear images and avoiding tissue damage. Proximity sensors can provide information about the distance to the surrounding tissue, which can help align the endoscope tip and navigate along curved paths. This paper presents a method of proximity measurement using capacitive sensors with active shielding to determine the radial distance between an endoscope and surrounding tissue. The capacitive sensor consists of four copper foil electrodes attached to a 9.5 mm diameter ring. Two different active shielding designs were investigated and compared to reduce the sensing angle and minimize lateral effects. Capacitance was measured as a function of distance using a linear stage. A MATLAB script controlled the linear stage and calculated the distance from the measured capacitance. The results showed that advanced active shielding could be useful to reduce the sensing angle (angular space where capacitance sensor detects capacitance changes.). This method provides a cost-effective solution for radial distance measurement in endoscopy, essential for improving diagnostic and therapeutic procedures.

Development of Optical Distance, Normal Force, Shear Force Sensor

Proximity and tactile sensors have been widely used to control robots. However, each of these sensors has its own shortcomings. Visual sensors have blind spots, whereas tactile sensors cannot acquire information when non-contact. To overcome these problems, this study develops an optical sensor that can measure the distance and two-axis forces using a beam structure and photo reflectors. The sensor is inexpensive owing to its simple structure. Moreover, the sensor is demonstrated to have sufficient accuracy for both the distance and force measurements at 0.2, 0.5, and 1.0 Hz. Additionally, the usefulness of the sensor is confirmed based on reduced impact control at the time of contact and force control.

Spatial pattern consistency and repeatability of proximal soil sensor data for digital soil mapping

AbstractData from proximal soil sensors can facilitate digital soil mapping at high spatial resolutions. However, their use for predicting static soil properties, such as texture, is affected by spatio‐temporal changes in environmental and measurement conditions. In this research study, seasonal changes in spatial patterns and repeatability of data provided by a platform that simultaneously measures the red (Red) and near infrared (NIR) reflectance, apparent soil electrical conductivity (ECa), temperature, and volumetric moisture content of topsoil (at 3–6 cm depth) were assessed. Test fields are located in Southern Finland with textures dominated by clay and fine sandy till. During single scans, mean relative differences between the data from duplicated measurement points ranged from ~4% to 6% and were the highest for temperature and Red values. The consistency of spatial patterns across seasons (spring and autumn 2021 and 2022) was the highest for ECa values, and the lowest for NIR. ECa and moisture were significant for predicting the clay contents at a cereal grain crop site, whereas temperature was significant at grass ley sites. Errors were generally lower when using spring data compared with autumn data (RMSE ranging from 4.8% to 11.1% for the data from different fields and measurement dates). For the fields, where static soil properties change at small spatial scales, spatially detailed moisture and temperature data support the understanding of seasonal changes in the spatial patterns derived from multi‐sensor data, and the corresponding changes in the performance of calibration models.

Automated smart waste segregation system using IoT technology

One of the major challenges faced not just by India but globally as well is waste management. India is the second most populous country and naturally generates tonnes of garbage daily. It is common to find dustbins overflowing with junk scattered everywhere, not to mention that segregation of waste is conveniently neglected. Many-a-times it is observed that despite providing separate bins for dry and wet trash, the convention is carelessly ignored. With the traditional methods of periodic garbage collection and manual segregation of wet, metallic, non-recyclable, and recyclable waste proving to be inefficient, there is a need for a better solution. With the help of IoT, a more effective solution is proposed to improve the current system and take a step forward toward the vision of smart cities. The proposed system uses smart garbage tracking, segregation, and collection systems, interfaced with ultrasonic sensors, rainfall/moisture sensors, inductive proximity sensors, and servo motors, along with the necessary hardware, with Arduino as the main controlling unit. The Arduino platform is used as a software platform for the working of the model and obtaining the expected results.