Proximity Sensors Research Articles

Alat Penghancur Kulit Kayu Manis Berbasis PLC

This study presents the design and development of an automated cinnamon bark shredder control system using a Programmable Logic Controller (PLC). The purpose of the system is to enhance production efficiency by replacing manual processes with automation, thereby reducing time, labor costs, and error rates. The system integrates components such as proximity sensors, induction motors, and PLC Omron CP1E, programmed with the CX-Programmer software. Testing demonstrated that the shredder effectively processes cinnamon bark into fine powder meeting Indonesian National Standards (SNI) for export, with consistent results in particle size (0.7–1 cm) and reduced waste. The tool is suitable for small and medium-sized industries (IKM) due to its cost efficiency, operational simplicity, and ability to improve production capacity. Future developments may focus on scaling up for industrial use.

Implementation of Conventional and Smart Weed Management Strategies in Sustainable Agricultural Production

ABSTRACTConventional weed management is known for the use of selective herbicides, tackling issues of herbicide‐resistant weeds, and endeavors to reduce reliance on herbicides, such as employing biological control of weeds and incorporating allelopathy. These strategies are integrated with traditional and other conventional weed management techniques. New challenges in agricultural production, such as declining population involved in agriculture, global warming, and climate changes make conventional weed management inadequate. Rapid advancements over the past decade in artificial intelligence (AI), unmanned aerial vehicles (UAVs), cameras, and sensors, necessitate the development and implementation of smart weed management (SWM) approaches for the 21st century. Wise weed management practices can control weeds and reduce emissions of methane (CH4), carbon dioxide (CO2), and nitrogen dioxide (NO2). Minimizing the use of herbicides in tandem with the application of smart technologies, like weed mapping and identifying spatial variability of weeds using proximal and remote sensors, multispectral and RGB cameras, can effectively manage weeds while also reducing labor costs. The SWM strategies also encompass the integrated use of organic herbicides, bioherbicidal products, and the judicious application of both organic fertilizers and inorganic fertilizers for weed management. Some approaches, such as alternate wetting and drying (AWD), can contribute to both SWM and carbon credits to farmers. The utilization of computing power, weed control robotics, and big data, combined with the education of the next generation of weed scientists and efforts to shift growers' attitudes and behaviors in weed management, may vary among countries. It requires active collaboration between agricultural extensionists and policymakers.

Pneumatic gripping system based on airflow proximity sensing and a self-feedback principle

Abstract. In pneumatic systems, the airflow circuit is both a driving source and a carrier of pressure, flow, and other information elements. In response to relying on electronic sensors and controllers to achieve closed-loop control in pneumatic systems, a theory of airflow proximity sensing and self-feedback drive was proposed to achieve closed-loop control. Based on the principle of airflow sensing, a new airflow proximity sensor was designed and studied. The structure was optimized using ANSYS software, and proximity sensing was achieved by increasing the pressure at the feedback port as the object approached. A self-feedback grasping pneumatic grasper was designed. The experimental results showed that the maximum grasping mass was 2.8 kg when the gas supply pressure was 0.1 MPa. The gripper could automatically sense and perform the grasping operation when it was close to the object.

A Proximity and Tactile Sensor with Visual Multiresponse.

Proximity and tactile multiresponse sensing electronic skin enriches the perception dimension, which is of great significance in promoting the intelligence of electronic skin. However, achieving real-time visualization in sensors such as proximity and tactile feedback remains a challenge. A proximity and tactile sensor with visual function is designed, which can realize optical early warning and electrical recognition when the object is near, and optical display and electrical output when the object is in contact. The sensing mechanism of the visual capacitive sensor is discussed, the detection range, linearity, sensitivity, and stability of the sensor are tested, and the relationship between force, capacitance, and light intensity is established. A 5 × 5 sensor array was prepared for object proximity detection and dynamic force trajectory detection. By combining machine learning to recognize optical information and electrical information, multifunctional intelligent human-computer interactive control is realized. Visual proximity and tactile sensors not only solve the real-time visualization challenge of tactile sensing but also promote the development of electronic skin to be multidimensional, multifunctional, and intelligent.

Development of an Aerial Manipulation System Using Onboard Cameras and a Multi-Fingered Robotic Hand with Proximity Sensors.

Recently, aerial manipulations are becoming more and more important for the practical applications of unmanned aerial vehicles (UAV) to choose, transport, and place objects in global space. In this paper, an aerial manipulation system consisting of a UAV, two onboard cameras, and a multi-fingered robotic hand with proximity sensors is developed. To achieve self-contained autonomous navigation to a targeted object, onboard tracking and depth cameras are used to detect the targeted object and to control the UAV to reach the target object, even in a Global Positioning System-denied environment. The robotic hand can perform proximity sensor-based grasping stably for an object that is within a position error tolerance (a circle with a radius of 50 mm) from the center of the hand. Therefore, to successfully grasp the object, a requirement for the position error of the hand (=UAV) during hovering after reaching the targeted object should be less than the tolerance. To meet this requirement, an object detection algorithm to support accurate target localization by combining information from both cameras was developed. In addition, camera mount orientation and UAV attitude sampling rate were determined by experiments, and it is confirmed that these implementations improved the UAV position error to within the grasping tolerance of the robot hand. Finally, the experiments on aerial manipulations using the developed system demonstrated the successful grasping of the targeted object.

Self-Powered, Flexible, Transparent Tactile Sensor Integrating Sliding and Proximity Sensing.

Tactile sensing is currently a research hotspot in the fields of intelligent perception and robotics. The method of converting external stimuli into electrical signals for sensing is a very effective strategy. Herein, we proposed a self-powered, flexible, transparent tactile sensor integrating sliding and proximity sensing (SFTTS). The principle of electrostatic induction and contact electrification is used to achieve tactile response when external objects approach and slide. Experiments show that the material type, speed, and pressure of the perceived object can cause the changes of the electrical signal. In addition, fluorinated ethylene propylene (FEP) is used as the contact electrification layer, and indium tin oxide (ITO) is used as the electrostatic induction electrode to achieve transparency and flexibility of the entire device. By utilizing the transparency characteristics of this sensor to integrate with optical cameras, it is possible to achieve integrated perception of tactile and visual senses. This has great advantages for applications in the field of intelligent perception and is expected to be integrated with different types of optical sensors in the future to achieve multimodal intelligent perception and sensing technology, which will contribute to the intelligence and integration of robot sensing.

A Hybrid Wind Retrieval Method Based on Least Square and Bayesian Estimation with Multiple Heterogeneous Sensors in Close Proximity

A Hybrid Wind Retrieval Method Based on Least Square and Bayesian Estimation with Multiple Heterogeneous Sensors in Close Proximity

Numerical simulation study on the voltage characteristics of proximity sensors in a hydraulic thrust reverser actuation system

Numerical simulation study on the voltage characteristics of proximity sensors in a hydraulic thrust reverser actuation system

Review on Forest Monitoring Rover

Automation is the process to reduce the man power and the idea of automation is to provide a test run in an Atmega328p microcontroller-based system to monitor and control the production operation. The main objective of this project is to control the electric power wastage and take data logs from a motor and also to check the performance of an employee in industries. This system works on Atmega328p microcontroller so it requires low cost and gives efficient performance in unnecessary electric power wastage in power loom motors. All the system is designed on basis of Atmega328p microcontroller, proximity sensor and RFID. The system includes IoT design to observe worker performance online from anywhere in the world.

Evaluation of Proximity Sensors Applied to Local Pier Scouring Experiments

Most pier scour monitoring methods cannot be carried out during floods, and data cannot be recorded in real-time. Since scour holes are often refilled by sediment after floods, the maximum scour depth may not be accurately recorded, making it difficult to derive the equilibrium scour depth. This study proposes a novel approach using 16 proximity sensors (VCNL4200), which are low-cost (less than USD 3 each) and low-power (380 µA in standby current mode), to monitor and record the pier scour depth at eight different positions in a flume as it varies with water flow rate. Based on the regression relationship between PS data and distance, the scour trend related to the equilibrium scour depth can be derived. Through the results of 13 local live-bed sediment scour experiments, this PS module was able to record not only the scour depth, but also the development and geometry of the scour under different water flows. Additionally, based on PS data readings, changes in the topography of the scour hole throughout the entire scouring process can be observed and recorded. Since the maximum scour depth can be accurately recorded and the scour trend can be used to estimate the equilibrium scour depth, observations from the experimental results suggest that the critical velocity derived by Melville and Coleman (2000) may have been underestimated. The experimental results have verified that, beyond achieving centimeter-level accuracy, this method also leverages the Internet of Things (IoT) for the long-term real-time observation, measurement, and recording of the formation, changes, and size of scour pits. In addition to further exploring scouring behavior in laboratory studies, this method is feasible and highly promising for future applications in on-site scour monitoring due to its simplicity and low cost. In future on-site applications, it is believed that the safety of bridge piers can be assessed more economically, precisely, and effectively.

DESIGN OF POLTEKSMART TRASH BIN: SOLUTION FOR WASTE MANAGEMENT IN AVIATION TRAINING COLLEGE

Waste management issues are a significant challenge in many major environments, including dormitory life in aviation vocational colleges. This study aims to design a prototype of a Polteksmart trash bin equipped with sensors and a Telegram Bot to manage waste in the dormitory building at Politeknik Penerbangan Palembang. This research and development (R&D) method using a 4D model started with data collection from literature review and observation. The research result is a smart design technology of a robot trash bin equipped with infrared sensors, proximity sensors, RTC sensors, EM4, and a Telegram Bot that sends notifications to mobile phones whenever trash capacity reaches 90%. The final design has been validated by a material expert and IT expert, and the analysis becomes quantitative data with assessment results both 90% means it very innovative and can be implemented. By implementing it, we hope to increase the effectiveness and efficiency of the waste sorting and management system. This implementation not only helps in reducing operational costs but also supports efforts to recycle and reuse organic waste that in line with goal to create a cleaner and healthier environment in the Politeknik Penerbangan Palembang. This research emphasizes the importance of technology integration in providing real-time waste management by making it easier for users to monitor the condition of the bins. As such, this research provides a strong foundation for future research to improve waste management's efficiency and effectiveness in educational settings.

Cyber policy for monitoring and regulating cyberspace and cyber security measures for combating technologically enhanced crime in South Africa

Advancements in science and technology has resulted in substantial transformations inside society. The telecommunications sector has established cyberspace, a virtual domain for online communication, data exchange, and digital interactions. This platform enables individuals to interact and cultivate relationships worldwide, fostering a sense of proximity despite geographical separation. Nonetheless, these improvements provide concerns, since there has been an increase in cyber victimisation via cyberspace, the internet, computer networks, and online systems. Criminals are progressively utilising these technologies to perpetrate illicit actions, endangering individuals, governments, organisations, and institutions.This study analyses the evaluation of cyber policies for regulating, monitoring, and supervising cyberspace activities, along with the implementation of cybersecurity measures to address technologically advanced crime. A mixed methods strategy, including qualitative and quantitative methodologies, was employed for data collecting. The research revealed that although cyberspace provides avenues for social contact, idea exchange, information dissemination, commercial transactions, and additional activities, it remains susceptible to cyber threats including ransomware, fraud, warfare, terrorism, trafficking, and breaches of privacy. Formulating cyber regulations to regulate actions in cyberspace is crucial for efficient law enforcement, alongside the establishment of a cybersecurity framework to safeguard critical cyber systems and bolster security protocols across several sectors. To safeguard both the public and private sectors against cybersecurity risks, it is essential to create and execute plans. These tactics encompass the regular evaluation and auditing of security systems, investment in cybersecurity training programs, maintenance of current systems, formulation and rehearsal of incident response plans, and dissemination of information among experts and professionals.

Can a Light Detection and Ranging (LiDAR) and Multispectral Sensor Discriminate Canopy Structure Changes Due to Pruning in Olive Growing? A Field Experimentation.

The present research aimed to evaluate whether two sensors, optical and laser, could highlight the change in olive trees' canopy structure due to pruning. Therefore, two proximal sensors were mounted on a ground vehicle (Kubota B2420 tractor): a multispectral sensor (OptRx ACS 430 AgLeader) and a 2D LiDAR sensor (Sick TIM 561). The multispectral sensor was used to evaluate the potential effect of biomass variability before pruning on sensor response. The 2D LiDAR was used to assess its ability to discriminate volume before and after pruning. Data were collected in a traditional olive grove located in Tenute di Cesa Farm, in the east of Tuscany, Italy, characterized by a 4x6 m planting layout and by developed plants. LiDAR data were used to measure canopy volumes, height, and diameter, and the generated point cloud was studied to assess the difference in density between treatments. Ten plants were selected for the study. To validate the LiDAR results, manual measurements of the canopy height and diameter dimensions of the plants were taken. The pruning weights of the monitored plants were obtained to assess the correlation with the canopy characterization data. The results obtained showed that pruning did not affect the results of the multispectral sensor, and the potential variation in canopy density and porosity did not lead to different results with this instrument. Plant volumes, height, and diameters calculated with the LiDAR sensor correlated well with the values of manual measurements, while volume differences between before and after pruning obtained good correlations with pruning weights (Pearson correlation coefficient: 0.66-0.83). The study of point cloud density in canopy thickness and height showed different shapes before and after pruning, especially in the former case. Correlations between point cloud density obtained from LiDAR and multispectral sensor results were not statistically significant. Even if more studies are necessary, the results obtained can be of interest in pruning management.

Automatic Modulation Recognition for Radio Frequency Proximity Sensor Signals Based on Masked Autoencoders and Transfer Learning

Automatic Modulation Recognition for Radio Frequency Proximity Sensor Signals Based on Masked Autoencoders and Transfer Learning

Integrated Grasping Controller Leveraging Optical Proximity Sensors for Simultaneous Contact, Impact Reduction, and Force Control

Integrated Grasping Controller Leveraging Optical Proximity Sensors for Simultaneous Contact, Impact Reduction, and Force Control

A Review on IOT based Power Loom Automation

Abstract: Automation is the process to reduce the man power and the idea of automation is to provide a test run in an Atmega328p microcontroller-based system to monitor and control the production operation. The main objective of this project is to control the electric power wastage and take data logs from a motor and also to check the performance of an employee in industries. This system works on Atmega328p microcontroller so it requires low cost and gives efficient performance in unnecessary electric power wastage in power loom motors. All the system is designed on basis of Atmega328p microcontroller, proximity sensor and RFID. The system includes IoT design to observe worker performance online from anywhere in the world.

The timing and spatial distribution of mother-offspring interactions in an obligate hider.

Parental care is indispensable for the survival and development of dependent offspring, often requiring a delicate balance of time and energy allocation towards offspring by parents. Among ungulates employing a hider strategy, deciding when and where to provide care while also maintaining a sufficient distance to not reveal the offspring´s hiding place is likely crucial in determining their fate. In this study, we analyzed the timing and spatial distribution of mother-offspring interactions in roe deer females (Capreolus capreolus L.). We fitted roe deer mothers and their neonates with GPS-collars combined with a proximity sensor in south Germany to address the spatial and temporal distribution of mother-fawn interactions during the first two months of the fawns' lives. We observed variations in the distance between mother and fawn, which initially increased over the first month and then decreased as the fawns grew older. The timing of mother-fawn contacts was strongly linked with the circadian rhythm of the mother, aligning closely with their typical bimodal activity peaks at dawn and dusk. Furthermore, we observed differences in habitat use between mother and offspring, reflecting the mother's requirements for food and protection (e.g. greater use of forests, higher distances to roads), as well as the fawn's priority requirement for protection (e.g. higher use of unmown grassland). We documented variations over time, highlighting how these requirements changed as the fawn ages. Interestingly, during the initial two weeks, most of the contacts occurred in habitats that were particularly favored by mothers. However, as the fawns aged, contacts occurred increasingly often in habitats that were routinely used by fawns. Understanding the timing, frequency, and spatial distribution of mother-offspring interactions provides valuable insights into the care strategies of hider ungulates. The observation that mothers leave their fawns in agricultural fields during the first few weeks of life has strong implications for wildlife management, as this behavior constitutes a kind of evolutionary trap under current agricultural practices and mowing regimes. Whether females can adjust their maternal care tactics to these novel selection pressures in human-altered landscapes is likely key to predicting the population dynamics of this obligate hider.

The function(s) of consciousness: an evolutionary perspective.

The functions of consciousness, viewed from an evolutionary standpoint, can be categorized as being either general or particular. There are two general functions, meaning those that do not depend on the particulars of how consciousness influences behavior or how and why it first evolved: of (1) expanding the behavioral repertoire of the individual through the gradual accumulation of neurocircuitry innovations incorporating consciousness that would not exist without it, and (2) reducing the time scale over which preprogrammed behaviors can be altered, from evolutionary time, across generations, to real-time. But neither answers Velmans' question, of why consciousness is adaptive in a proximate sense, and hence why it would have evolved, which depends on identifying the particular function it first performed. Memory arguably plays a role here, as a strong case can be made that consciousness first evolved to make motivational control more responsive, though memory, to the past life experiences of the individual. A control mechanism of this kind could, for example, have evolved to consciously inhibit appetitive behaviors, whether consciously instigated or not, that would otherwise expose the individual to harm. There is then the question of whether, for amniote vertebrates, a role in memory formation and access would have led directly to a wider role for consciousness in the way the brain operates, or if some other explanation is required. Velmans' question might then have two answers, the second having more to do with the advantages of global oversight for the control of behavior, as in a global workspace, or for conferring meaning on sensory experience in a way that non-conscious neural processes cannot. Meaning in this context refers specifically to the way valence is embodied in the genomic instructions for assembling the neurocircuitry responsible for phenomenal contents, so it constitutes an embodied form of species memory, and a way of thinking about the adaptive utility of consciousness that is less concerned with real-time mechanistic events than with information storage on an evolutionary time scale.

Utilizing smartphone proximity sensor to analyse accelerated motion of object in an inclined plane and determine the acceleration and kinetic friction coefficient

Abstract In this work, we launched smartphones with a moving object to analyse the motion on an inclined plane. The data of time versus distance was acquired by utilizing a smartphone proximity sensor to record time intervals between detection objects whose distance had been set beforehand. The plot of time versus distance was used to analyze the characteristics of accelerated motion. Meanwhile, time squared versus distance was used to determine acceleration. The inclination angle was varied to observe the effect on the motion characteristic and acceleration value. Furthermore, kinetic friction coefficient existing along the object’s motion was also calculated.

Transportation Mode Detection Using Learning Methods and Self-Contained Sensors: Review.

Due to increasing traffic congestion, travel modeling has gained importance in the development of transportion mode detection (TMD) strategies over the past decade. Nowadays, recent smartphones, equipped with integrated inertial measurement units (IMUs) and embedded algorithms, can play a crucial role in such development. In particular, obtaining much more information on the transportation modes used by users through smartphones is very challenging due to the variety of the data (accelerometers, magnetometers, gyroscopes, proximity sensors, etc.), the standardization issue of datasets and the pertinence of learning methods for that purpose. Reviewing the latest progress on TMD systems is important to inform readers about recent datasets used in detection, best practices for classification issues and the remaining challenges that still impact the detection performances. Existing TMD review papers until now offer overviews of applications and algorithms without tackling the specific issues faced with real-world data collection and classification. Compared to these works, the proposed review provides some novelties such as an in-depth analysis of the current state-of-the-art techniques in TMD systems, relying on recent references and focusing particularly on the major existing problems, and an evaluation of existing methodologies for detecting travel modes using smartphone IMUs (including dataset structures, sensor data types, feature extraction, etc.). This review paper can help researchers to focus their efforts on the main problems and challenges identified.