Light Intensity Sensor Research Articles

10-[(4-Cyanobenzylidene)]-Anthracen-9(10H)-One: syntheses, characterization and application in UV light detection

In this work, the compound 10-[(4-cyanobenzylidene)]-anthracen-9(10H)-one (1) has been synthesized from the corresponding anthrone and 4-cyanobenzaldehyde. It has been characterized by nuclear magnetic resonance (NMR), infrared spectroscopy (IR), high-resolution mass spectroscopy (HRMS) and single-crystal X-ray diffraction (XRD) analysis. Moreover, square wave voltammetry (SWV) was performed to determine the HOMO and LUMO potential levels of the anthrone derivative 1, which indicates that sensitization of TiO2-based electrodes is thermodynamically feasible. Therefore, this characteristic of compound 1 allowed its incorporation in a Grätzel-type solar cell. Photocurrent density measurements under UV irradiation are proportional to the light source intensity, and the operational parameters of the photoelectrochemical cell are relatively stable over time. In fact, the sensitivity of the generated photocurrent normalized by the supplied irradiance for TiO2-1 (7.73 µA/mW) as a photoanode is higher than that of TiO2 alone (5.14 µA/mW), indicating the improvement that 1 provides to TiO2 with respect to UV light detection. The higher photocurrent and the improved stability due to the implementation of 1 are very promising for possible applications as a sensitizer for UV light intensity sensors in dye-sensitized solar cells (DSSC).

All-fiber light intensity sensor employing a three-core fiber taper integrated by magnetic fluids

An all-fiber optic light intensity sensor employing a three-core fiber (TCF) taper integrated by magnetic fluids (MFs) is proposed and fabricated. The three-beam interference and evanescent field characteristic of the TCF taper are combined with the laser-generated photothermal effect of the MFs for the first time. The effect of irradiation laser intensity on the interference spectrum of the proposed sensor is investigated experimentally. According to the experimental results, the interferential transmission spectrum is susceptible to the irradiation laser intensity. Under 473 nm laser irradiation, the maximum laser intensity sensitivity reaches −1.64425 nm/(mW/mm2). Moreover, the modal coupling processes of the TCF before and after tapering are investigated experimentally and by simulation. The proposed sensor is attractive because of its sensitive light response, simple structure, easy fabrication, and compact size. This work gives a significant reference for the manufacture and application of optically controlled microfluidic devices integrated by MFs.

Automated Fault Detection and Location Monitoring of Street Lights in Smart Cities

This work will implement an automated fault detection and monitoring system for streetlights in smart cities. The system will use smart streetlights with sensors, communication modules, and intelligent controllers to create a sensor network across the city. These sensors, like light intensity, motion, and temperature sensors, will collect real-time data on the status of street lights and the environment. The data will be analyzed by a centralized monitoring system that will use algorithms to detect abnormalities in the sensor data that may indicate faults or malfunctions in the street lighting infrastructure. GPS tracking technology will be used to pinpoint the location of each street light. An automated alert system will notify maintenance teams and city officials through a webpage if a fault is detected. The system will also use historical data to anticipate potential issues before they arise.The benefits of this system include improved energy efficiency, cost savings through timely maintenance, quick response times for fault resolution, and data-driven decisionmaking for urban planning. It will provide real-time information on the status of street lights and their environment, which can be used to optimize energy consumption and reduce costs. The system will also enable city officials to make data-driven decisions for urban planning. Ultimately, this system will help to create smarter and more sustainable cities by enhancing public safety, optimizing energy consumption, and ensuring the reliability of street lighting infrastructure. The system will provide a more efficient and costeffective approach to street lighting maintenance, leading to better services for citizens.

Portable Arduino-Based Multi-Sensor Device (SBEDAD): Measuring the Built Environment in Street Cycling Spaces.

The built environment's impact on human activities has been a hot issue in urban research. Compared to motorized spaces, the built environment of pedestrian and cycling street spaces dramatically influences people's travel experience and travel mode choice. The streets' built environment data play a vital role in urban design and management. However, the multi-source, heterogeneous, and massive data acquisition methods and tools for the built environment have become obstacles for urban design and management. To better realize the data acquisition and for deeper understanding of the urban built environment, this study develops a new portable, low-cost Arduino-based multi-sensor array integrated into a single portable unit for built environment measurements of street cycling spaces. The system consists of five sensors and an Arduino Mega board, aimed at measuring the characteristics of the street cycling space. It takes air quality, human sensation, road quality, and greenery as the detection objects. An integrated particulate matter laser sensor, a light intensity sensor, a temperature and humidity sensor, noise sensors, and an 8K panoramic camera are used for multi-source data acquisition in the street. The device has a mobile power supply display and a secure digital card to improve its portability. The study took Beijing as a sample case. A total of 127.97 G of video data and 4794 Kb of txt records were acquired in 36 working hours using the street built environment data acquisition device. The efficiency rose to 8474.21% compared to last year. As an alternative to conventional hardware used for this similar purpose, the device avoids the need to carry multiple types and models of sensing devices, making it possible to target multi-sensor data-based street built environment research. Second, the device's power and storage capabilities make it portable, independent, and scalable, accelerating self-motivated development. Third, it dramatically reduces the cost. The device provides a methodological and technological basis for conceptualizing new research scenarios and potential applications.

GUARDIAN OF THE GHATS AND HEADLIGHTS FOR VISIBILITY

The abstract introduces a ground breaking project aimed at revolutionising road safety through adaptive lighting and collision detection in challenging driving environments. In the contemporary context, road accidents pose a significant threat to public safety, with statistics revealing a staggering number of incidents globally. According to recent data from the World Health Organization (WHO), over 1.3 million people die each year in road traffic accidents, and an additional 20 to 50 million suffer non-fatal injuries. A substantial portion of these accidents occurs during turns in hilly terrains, highlighting the need for innovative solutions. This project addresses the aforementioned issue by proposing a dynamic lighting system that utilises light intensity sensor to sense oncoming vehicle headlights. By adjusting the brightness of our vehicle's LED lights in response to detected light intensity, the system aims to reduce the risk of blinding oncoming drivers, thereby mitigating the likelihood of accidents. Furthermore, the introduction of Ghats Section Collision Detection using Infrared (IR) sensors enhances safety during turns. In Ghats sections, where accidents are more prevalent, IR sensors strategically placed on each side of the car detect potential collisions and activate warning indicators, such as a red light, to alert the driver. This dual-feature system provides a comprehensive approach to address the complex challenges associated with road safety, offering a promising solution to reduce accident rates and enhance overall driving experience.

Photosvaltable Characteristics Monitoring System Using the Internet of Things (IOT)


 
 
 
 Continuous monitoring of solar panel performance is essential to ensure effective and efficient generation of electrical energy. Developing a monitoring system such as an I-V characteristic curve tracker enables real-time monitoring and identification of potential problems or efficiency improvements. The system utilizes a circuit switching system for accurate and continuous measurement, providing insight into how the solar panel responds to changing environmental and load conditions. The data recorded by temperature, light intensity, current, and voltage sensors on the solar panel provides valuable information about its condition and the environmental factors affecting it. Utilizing IoT technology allows real-time monitoring of the data, accessible via a web page and presented graphically. The data is also stored in Excel format for further analysis, so users can access and monitor continuously as long as they are connected to the internet. From the experimental results, the Voc of the solar panel ranged from 18.7 V to 20.42 V, and Isc between 0.0727 A to 0.2145 A, which were tested under solar irradiation ranging from 100 to 500 W/m². This research demonstrates the importance of continuous monitoring and the effectiveness of the developed monitoring system in providing real-time data for analysis and optimization of solar panel performance. The system has been tested to meet the IEC No. 13B-23 standard for accuracy classes 0.2 and 0.5. A comparison between manual testing and sensor testing shows that despite the difference in accuracy levels, the sensor measurements have a relatively low average error (1.04% for voltage and 0.64% for current) compared to manual measurements, indicating that the sensor is reliable in providing accurate data. This demonstrates the reliability and effectiveness of using the sensor in the solar panel characteristics monitoring system.
 
 
 

Design of a Smart Lighting System Based on Sensor Integration and Automation

As a crucial application of modern technology, smart lighting systems are transforming our interaction with the living environment. The key lies in utilizing advanced sensor technology to maximize lighting efficiency and conserve energy. This paper focuses on designing a sensor-based lighting control system that integrates Passive Infrared and light intensity sensors for the automated management of environmental lighting. Our research has extensively explored the integrated application of PIR and light-intensity sensors. The design aims to automatically adjust indoor lighting based on environmental light conditions and the presence or absence of occupants to enhance comfort and energy efficiency. The sensor fusion algorithm was optimized through a series of experiments to improve detection accuracy and effective energy utilization. Based on the design analysis, the system can significantly enhance energy savings by reducing unnecessary lighting without compromising occupant comfort. The system’s design also considers rooms of varying sizes and layouts, demonstrating good adaptability and versatility. The significance of this research lies in providing innovative solutions for the smart lighting domain. By enhancing the intelligence and responsiveness of lighting systems in home and commercial environments, our design offers a more intuitive and energy-efficient lighting experience. It paves the way for future developments and innovations in lighting systems. This work highlights the immense potential of sensor-based systems in creating interactive and adaptive environments suitable for diverse settings such as homes, corridors, and underground garages.

Microprocessor-based photometric light intensity sensor for airport lamps quality testing

Microprocessor-based photometric light intensity sensor for airport lamps quality testing

Optimizing Solar Energy Harvesting: An Arduino-Enhanced Dual-Axis Tracking System

Technological progress is enhancing the accessibility and potential of solar energy as a renewable source. This paper introduces a strategy leveraging Ohm's law and the power equation to derive additional energy from solar photovoltaic (PV) panels. The proposed method involves the integration of an automated solar tracking system employing both dualaxis and polar single-axis configurations. This system is comprised of a stationary vertical axis and a flexible horizontal axis, both under motor control. To enhance power output and efficiency, the trackers autonomously follow the sun, constantly adjusting the solar panel positions. The tracking system self-adjusts in the event of a 2 to 3-degree misalignment to minimize power loss due to continuous motor operation. Light intensity sensors analyze illumination levels on each side, guiding the panels toward the light source. The tracking motion continues until equal light exposure on both sides is detected, leading to an enhanced solar irradiance for the panels

PENERAPAN SENSOR CJMCU101 UNTUK MENDUKUNG SISTEM SMART LECTURE ROOM

This study presents the design of a Smart Lecture Room system that utilizes light intensity sensors, specifically CJMCU101. These sensors are installed in each classroom to monitor the ambient conditions. The implementation of the designed system was carried out in the classrooms of the Udayana University Electrical Engineering Study Program. To achieve this goal, the classroom utilized by the Electrical Engineering Study Program of Udayana University was divided into two classes (DH101 and DH102) and a sensor was installed in each class as an IoT device. The IoT devices are connected to a Raspberry Pi Access Point, where the data from the sensors is stored and monitored using the Thinger.io platform. The validation of the sensor testing is carried out by comparing the results obtained from the sensors with the results obtained from a thermohygrometer measurement. This research produces a prototype smart lecture system, applied to a classroom mockup, that employs IoT devices, sensor databases, and sensor monitoring. The data from each sensor's detection is stored in the LAMP database, which employs Linux, Apache, MySQL, and PHP. The Thinger.io platform monitors the values of each sensor. A variation in accuracy between the sensor and measuring instrument results in a difference in their values. The CJMCU101 light intensity sensor has an average accuracy of 93.48% compared to the measuring instrument on DH101. The average accuracy of the sensor value compared to the measuring instrument on DH102 is 95.96%.

DEVELOPMENT OF DC-DC BUCK CONVERTER FOR SOLAR PANEL ENERGY STORAGE THROUGH LOAD OPTIMIZATION AND FEEDBACK CIRCUIT

Solar panels are crucial components in converting sun radiation into electrical energy through the photovoltaic effect. A solar panels cannot be connected directly to the load due to its low energy conversion efficiency and low output voltage. One of the methods used to control solar cells to operate efficiently at their maximum power point is MPPT. In this paper, we design a DC-DC converter by modifications of the Butterworth filter circuit and feedback circuit in the MPPT system for storing solar panel electrical using the Hill Climbing (HC) method. The device consists of a DC-DC buck converter circuit, two pieces of INA219 sensors, a DS18B20 temperature sensor, a MAX44009 light intensity sensor, a SD card module and a DS3231 RTC. The DC-DC buck converter circuit simulation is carried out to determine the optimal load. The load optimization was conducted by analyzing the AC simulation using Ltspice software. The magnitude of the output voltage ripple in nine different loads was observed. From the simulations performed, it was found that the 50 Ω load has an output voltage ripple of 8.96 mV and is smaller than the other loads. The main DC-DC buck converter circuit is designed using a butterworth low pass filter with a cut-off frequency of 1000 Hz (R = 50 Ω, L = 33.8 mH and C = 750 nF) and a feedback circuit with a cut-off frequency of 500 Hz is added. From the prototype measurement, it was found that the average output power was 3249,7 milliwatts and the average input power was 4779 milliwatts, thus the average efficiency was 68%. With these results, the DC-DC converter circuit configuration is suitable for use in electrical energy storage systems from solar panels that have high efficiency.

A Smart Kumbung For Monitoring and Controlling Environment in Oyster Mushroom Cultivation Based on Internet of Things Framework

Oyster mushroom (Pleurotus Ostreatus) is a fungus-like plant that is often cultivated in Indonesian agriculture. Oyster mushroom is raised by manipulating environmental parameters, so that it can grow in the provided Kumbung. Oyster mushroom requires a temperature that is used, which ranges from 23°-28°C, for humidity used between 70% -90% and for light intensity it requires light of ±300 lux. In this study, a system was designed to carry out automatic monitoring and control in real time based on the Internet of Things (IoT) which integrates DHT22 humidity and temperature sensors, BH1750 light intensity sensors and NodeMCU as a microcontroller with measurement results sent to the Firebase database. In addition, a water pump connected to the sprayer nozzle is installed in this system to maintain the humidity of the oyster mushroom curd. From the test results, the system can work automatically to stabilize temperature, humidity, and light intensity according to the ideal parameters.

Energy and exergy analysis with cost-efficiency comparison of modified phase change material (PCM) integrated with solar panel thermal system

This study investigates the efficiency and cost-effectiveness of integrating Phase Change Materials (PCMs) into solar panels to optimize power output and power conversion efficiency under varying temperature conditions. By applying PCMs, temperature fluctuations can be reduced, maintaining solar panels at an optimal temperature for power generation. The research employs modeling and simulation techniques, focusing on energy and exergy analysis of solar energy storage systems based on pure and modified PCMs such as Paraffin wax, Sodium acetate trihydrate, Sodium sulfate decahydrate, etc. Temperature and light intensity data are collected in the Wangchan district, Rayong province, using a light intensity sensor and a thermocouple. The study analyzes each layer of the solar panel, employing numerical methods and matrix solutions to solve the system of non-algebraic equations, yielding temperature values for each component layer. The thermodynamic properties of the modified PCMs are calculated theoretically, and their cost-efficiency is analyzed by comparing the solar panel’s increased power area density generation after applying specific PCMs to the cost of the PCM. The simulation results demonstrate that the solar panel integrated with PCM generates up to 11.1% more power than a regular solar panel, assuming negligible heat loss from the sides of the solar panel and an average temperature during the melting and solidification processes for the PCMs. Moreover, the best cost-efficiency of the modified PCM is achieved, with an increase of up to 637.7%, using a combination of paraffin wax and polyethylene glycol.

Scarab Beetle‐Inspired Embodied‐Energy Membranous‐Wing Robot with Flapping‐Collision Piezo‐Mechanoreception and Mobile Environmental Monitoring

AbstractThe mechanoreception system in bionic micro air vehicles, akin to insect sensory neurons, handles internal and external stimulus information. However, current onboard mechanoreception methods add weight and necessitate additional power. Employing the embodied energy design paradigm, a lightweight intelligent membranous wing is proposed, mimicking the scarab beetle's hindwing morphology and kinematics. This wing serves multiple functions, including aerodynamic load‐bearing, flight piezo‐mechanoreception, and power supply. The beetle's semi‐tubular costa structure is replicated, featuring a compliant leading edge for upstroke aerodynamic load resistance. Inspired by beetle hindwing veins and membranes, the bionic wing with three membranous fields: anal, medial, and apical, using heat lamination of multilayer materials is fabricated. The bionic wing's aerodynamic performance closely mirrors that of a real beetle hindwing, enabling various flight maneuvers and validating its real‐flight potential. As a piezo‐mechanoreception receptor for micro air vehicles, the bionic intelligent wing senses flapping frequency, wing deformations, and collisions through voltage signals from piezoelectric materials in the three membranous fields. Energy harvested from flapping‐wing motion powers onboard light intensity and ultraviolet sensors for mobile 3D environmental monitoring. This integration of aerodynamics, mechanoreception, and power supply via embodied flapping energy offers a novel approach for designing future intelligent flapping‐wing micro air vehicles.

Variation in women’s attitudes toward intimate partner violence across the rural–urban continuum in Ethiopia

Little is known about the effects of urbanization on women’s attitudes toward intimate partner violence (IPV). The scarcity of empirical studies on this relationship can be partly attributed to the lack of an objective measure of urbanization levels. In this study, we investigate the effects of urbanization on Ethiopian women’s attitudes toward IPV using four continuous measures of urbanization: nightlight intensity, distance to urban areas, total urban area within a 10-km radius, and an urbanization index. These measures are defined from satellite-based nighttime light intensity and multispectral sensor data. We find that despite a generally strong positive association between urbanization and progressive attitudes among women toward IPV, some stages of urbanization show a more significant association than others. The heterogeneities in the effect of all urbanization measures on women’s attitudes toward intimate partner violence further show that the effects of urbanization measures are sharply heterogeneous across wealth indicator terciles. While we find that urbanization measures are associated with an overall decrease in the justification of IPV, the effects are higher and stronger for women in the upper and middle wealth terciles compared to the lowest wealth tercile. Initially less-privileged women gain little from urbanization in the attitudes toward IPV, resulting in increased inequality in women’s empowerment in the short and medium term.

Development of public lighting system with smart lighting control systems and internet of thing (IoT) technologies for smart city

This study proposes the design and development of public light systems integrated with Internet of Things (IoT) applications for smart cities. Smart public lighting systems are designed using LED light sources in combination with a controller based on light intensity and motion sensors to control the brightness in working areas as per standard requirements. The control of smart public lighting systems is designed to operate in three modes: manual, scheduled, and auto modes, which are tested and compared in terms of lighting and power quality. Other functions of IoT, such as air pollution detection, security system-based video surveillance, and warning systems for flood disasters, are integrated into smart public lighting systems. A prototype of the designed smart public lighting system is presented in this paper. The parameters of average illuminance, overall uniformity, and threshold increment were implemented using DIALux software to optimise the luminaire spacing. The results showed that the goal of energy saving could be achieved using the auto mode. Although the automatic mode caused current harmonic distortion to the electrical grid, the harmonic value was less than the specified standard. Furthermore, the precision of IoT system operation was dependent on environmental variations and the reliability of wireless network technology.

Design of the Urban Lighting Control System Based on Optical Multisensor Technology and the GM Model

Lighting has emerged as a central concern in the domain of city planning and design in recent decades. Better lighting does more than just make cities safer and more secure; it also makes them more aesthetically pleasing and easier to live in. A single type of optical sensor is no longer sufficient to meet the needs of intelligent lighting for urban roads, and as such, there is a growing demand for cutting-edge control systems that can adapt to the dynamic lighting needs in urban environments. This paper’s goal is to create an intelligent urban lighting control system by integrating optical multisensor technology and the gray model (GM model). Programmable logic controller (PLC) serves as the system’s central processing unit, with light intensity sensors and color sensor-detecting devices placed strategically throughout each city and linked directly to the controller. Each road streetlight is equipped with a motion sensor detection device that is tasked with identifying the presence of vehicles and pedestrians within its field of view. Data fusion technology is utilized to process the environmental data gathered by optical multisensors, the collected data are then used to control and predict outcomes using the robust prediction capability of the GM model, and the result is a lighting control strategy that is both efficient and intelligent. In the end, the strategy presented in this paper is applied to improving the management of an industrial park lighting system’s energy consumption. The results of the evaluations show that the fresh method is successful in dimming, prediction, and control. This conclusively demonstrates the efficacy of the paper’s proposed design solution, which integrates optical multisensor technology with sophisticated control algorithms and data analysis to improve the quality of life in urban areas by boosting the efficiency and sustainability of the urban lighting system.

Optimizing Urban Street Lighting: A Smart Approach using IOT

Abstract: This project presents a street light detection system using Arduino, LED, LDR (Light Dependent Resistor), IR (Infrared) sensors, resistors, and a breadboard. The aim of the project is to automate street lighting based on the ambient light conditions, thereby optimizing energy consumption and enhancing safety. The system utilizes LDRs to measure the ambient light intensity and IR sensors to detect the presence of vehicles or pedestrians. The Arduino microcontroller processes the sensor inputs and controls the operation of the streetlights accordingly. The system incorporates a breadboard for easy prototyping and connectivity. Upon detecting low ambient light levels and the absence of vehicles or pedestrians, the Arduino triggers the LED street lights to turn on. Conversely, when the ambient light levels are high or a vehicle or pedestrian is detected, the Arduino instructs the LEDs to turn off, conserving energy and reducing light pollution. To ensure accurate light detection, appropriate resistors are used to calibrate the LDRs and IR sensors. This allows for precise measurement and detection thresholds, enhancing the reliability of the system.

Designing, Optimizing, and Validating a Low-Cost, Multi-Purpose, Automatic System-Based RGB Color Sensor for Sorting Fruits

The use of automatic systems in the agriculture sector enhances product quality and the country’s economy. The method used to sort fruits and vegetables has a remarkable impact on the export market and quality assessment. Although manual sorting and grading can be performed easily, it is inconsistent, time-consuming, expensive, and highly influenced by the surrounding environment. In this regard, this study aimed to design and optimize the performance of a low-cost, multi-purpose, automatic RGB color-based sensor for sorting fruits. The proposed automatic color sorting system consists of hardware components including a machine frame, belt and pulleys, conveyor belt, scanning zone, plastic boxes, electric components (stepper motors, RGB color sensors, Arduino Mega, motor drivers), and software components (Arduino IDE version 2.2.1 and C++). Calibration was performed for the light intensity sensor to measure the light intensity inside the scanning zone, the conveyor speed sensor, and the RGB color sensors by testing the RGB color channels. The sensor, the height, conveyor belt color, and light intensity should be carefully adjusted to ensure a high performance of the color-based sorting system. The results showed that the appropriate sensor height ranged from 15 to 30 mm, the optimum color of the conveyor belt was black, and scanning the objects at a light intensity of 25 lux achieved the best output signals. The RGB color sensors achieved an analytical performance similar to that obtained with manual sorting without requiring the use of computers for image processing like other automatic sorting systems do in order to gather RGB data.

Perbandingan Nilai Daya Luaran Panel Surya Kapasitas 50Wp Terhadap Posisi Reflektor Cermin Datar

Solar panel systems are widely used to meet energy needs at this time. Solar panels have optimal power for 4 hours, namely 10:00 to 14:00. but this is still said to be not optimal if the angle of the static solar panels does not follow the movement of the sun. This can also be caused by weather factors that are covered in clouds. Previous research conducted by Tri Wahyu Ardianto used mirror reflectors but was not equipped with sensors and data storage. Based on this, to optimize solar panel energy, a flat mirror reflector design for solar panels has been made, equipped with four flat mirror reflectors on each side to form a large square. The solar panel is placed in the middle between the four flat mirrors. In this study, the measurement of electric power was carried out by carrying 3 variable angles for reflector positions, namely 0°, 60°, and 70°. The decision of the three reflector positions is made to find out the ratio of the maximum output power values. This system is also equipped with current, voltage, and light intensity sensors. The results show that the maximum output power of solar panels is shown at the reflector position of 60° with an average power output of 19.70 Watt followed by a reflector position of 70° with an average output power of 19.18 Watt and finally the reflector position is 0° with an average output power value of 14.87 Watt.