Light Intensity Data Research Articles

Regional assessment of human-caused ecological risk in the Poyang Lake Eco-economic Zone using production-living-ecology analysis.

In this study, based on the regional land-use risk space division (regional ecological risk source/receptor space identification) using production–living–ecology analysis, three spatial function indexes, i.e., production, living, and ecology function indexes, were proposed for regional ecological risk assessment (RERA) with respect to human disturbance. The first two indexes can be regarded as regional ecological risk source indexes, whereas the final index can be regarded as a regional ecological risk receptor index. Using an artificial assignment method based on the land-use types and Defense Meteorological Program Operational Line-Scan System (DMSP/OLS) nighttime light intensity data, these three spatial function indexes were effectively manifested. By incorporating these indexes with eco-environmental vulnerability proxies, an RERA framework was established and applied in the Poyang Lake Eco-economic Zone (PLEZ), which is an ecological-protection and economic-development coordination-oriented region in China. The results suggest that (1) the DMSP/OLS nighttime light intensity data correlated well with the spatial distribution of regional urban/town areas; consequently, it was reasonable to use this dataset for representing regional production-living function space (urban/town area). (2) Overall, the forestlands and winter waterbodies of Poyang Lake were in the high-risk grade, and so did the Nanchang City construction land area; in contrast, the final risk levels of winter wetlands and croplands were relatively low. (3) Owing to the highest human disturbance (including both production and consumption human activities) and eco-environmental vulnerability level, urban/town areas such as Nanchang City had the highest final risk grade. (4) The low, medium, high, and very high-risk grades accounted for 21.22%, 39.53%, 36.31%, and 2.94% of the region, respectively. I believe that the proposed land use function indexes will be helpful in conducting human-caused RERA research in the future. Furthermore, the assessment results can provide a scientific basis for regional ecological risk management within the PLEZ.

Quantifying the influence of location of residence on blood pressure in urbanising South India: a path analysis with multiple mediators

Abstract Objectives: The current study aims to estimate the causal effect of increasing levels of urbanisation on mean SBP, and to decompose the direct and indirect effects via hypothesised mediators. Methods: We analysed data from 5, 840 adults (≥ 18 years) from the Andhra Pradesh Children and Parents study (APCAPS) conducted in 27 villages in Telangana, South India. The villages experienced different amounts of urbanisation during preceding decades and ranged from a rural village to a medium sized town. We estimated urbanisation levels of surveyed villages by combining remote sensing data of night-time light intensity (NTLI), measured by unitless digital numbers, with satellite imagery and ground surveying of village boundaries. We performed mediation analysis using linear mixed-effects models with SBP as the outcome, log-transformed continuous NTLI as the exposure, and three composite mediators summarising information on (i) socio-demographics (e.g., occupation and education); (ii) lifestyle and mental health (e.g., diet and depression); (iii) metabolic factors (e.g., fasting glucose and triglycerides). All models fitted random intercepts to account for clustering by villages and households and adjusted for confounders. Results: The NTLI range across the 27 villages was 62 to 1081 (4.1 to 7.0 on the log scale). Mean SBP was 122.7 mmHg (±15.7) among men and 115.8 mmHg (±14.2) among women. One unit (integer) log-NTLI increase was associated with a rise in mean SBP of 2.1 mmHg (95% CI 0.6, 3.5) among men and 1.3 mmHg (95% CI 0.0, 2.6) among women. We identified a positive indirect effect of log-NTLI on SBP via the metabolic pathway, where one log-NTLI increase elevated SBP by 4.6 mmHg (95% CI 2.0, 7.3) among men and by 0.7 mmHg (95% 0.1, 1.3) among women. There was a positive indirect effect of log-NTLI on SBP via the lifestyle and mental health pathway among men, where one log-NTLI increase elevated SBP by 0.7 mmHg (95% CI 0.1, 1.3). Observed negative direct effects of log-NTLI on SBP and positive indirect effects via the socio-demographic pathway among both genders; as well as a positive indirect effect via the lifestyle and mental health pathway among women, were not statistically significant at the 5% level. The sizes of effects were approximately doubled among participants ≥40 years of age. Conclusion: Our findings offer new insights into the pathways via which urbanisation level may act on blood pressure. Large indirect effects via metabolic factors, independent of socio-demographic, lifestyle and mental health factors identify a need to understand better the indirect effects of environmental cardiovascular disease (CVD) risk factors that change with urbanisation. We encourage researchers to use causal methods in further quantification of path-specific effects of place of residence on CVDs and risk factors. Available evidence-based, cost-effective interventions that target upstream determinants of CVDs should be implemented across all socio-demographic gradients in India.

Genetic analysis with pyrosequencing using loop pipetting and a light dependent resistor.

DNA sequencing is among the most important techniques in biology to decipher the key genetic players of health and disease. The existing laboratory instruments for DNA sequencing are well established and reliable. However, these instruments are still out of reach of most laboratories in the world due to very high equipment and running costs and require trained personnel to keep them running. These instruments are also large and bulky making them unsuitable for analysis in remote settings away from laboratories. Here we describe a proof-of-concept of a DNA sequencing device LoopSeeq using a simple approach to address the said problems without minimizing the quality of results. The device was designed to perform pyrosequencing by iterative addition of dNTPs by contact dispensing through a loop pipette (loopette) and detection of chemiluminiscence with the cheapest sensor in the market, a light dependent resistor (LDR). Two small geared motors drive the moving parts in a controlled and coordinated manner with the help of a motor driver circuit, an Arduino Nano microcontroller and two small neodymium magnets. The real-time light intensity data from the LDR were transferred to a laptop computer for further analysis. Pyrosequencing was optimized using 55 nt self-primed oligo. In order to demonstrate the DNA sequencing ability with real samples, molecular genetic analysis was performed for a previously identified novel mutation from our lab in exon4 of the OCA2 gene. LoopSeeq successfully identified the homozygous normal (c.408-409_AA), homozygous mutant (c.408-409_delAA) and heterozygous carrier (c.408-409_AA/delAA) alleles in three individuals of a family affected with oculocutaneous albinism (OCA). Further, this can be implemented for molecular diagnostic applications for bacterial, viral or other pathogen detection and genotyping among different subtypes following some reports described earlier. A few drawbacks in the current implementation including the evaporation of liquid reagents, possible loopette contamination, etc. associated with use for longer times are also described along with suggestions to rectify these problems in future designs. With the described capabilities, the LoopSeeq device can be implemented in routine labs as well as in several real-world situations where conventional DNA sequencing instruments are unfeasible, for example, diagnostic testing at remote settings or at the point-of-care.

Study of urban heat island index methods for urban agglomerations (hilly terrain) in Chongqing

To study the urban heat island (UHI) effect in the mountainous areas of Chongqing, the UHI indexes for the Chongqing urban agglomerations were investigated in the present study. This study is based on data from 34 national weather stations and more than 2000 regional automated weather stations in Chongqing, Defense Meteorological Satellite Program/Operational Linescan System (DMSP/OLS) nighttime light data, and 30-m high-resolution land use data and Moderate Resolution Imaging Spectroradiometer (MODIS) land surface temperature remote sensing data for Chongqing in 2015. Moreover, the influences of three background temperature calculation methods on the UHI effect were compared. The results showed that, if only the land use data and the city clustering algorithm (CCA) were used to divide the urban and suburban areas, the strong UHI index of Chongqing exhibited an abnormal increase in the years with extremely high temperatures, and the corresponding divided suburban and urban areas had relatively large differences in altitudes, thereby overestimating the UHI index. Therefore, in the present study, a new method for dividing the urban and suburban areas based on the combined CCA and light intensity data and a division method with the altitudes calibrated on this basis were designed. Both methods were able to satisfactorily reduce the influence of extreme climate years and excessively large differences in altitudes on the UHI index calculations and provide a new approach for future studies of the UHI index for mountainous areas with large altitude differences.

Adaptive Classroom Berbasis IoT (Internet Of Things), Saklar Lampu Berdasarkan Keberadaan Seseorang Dan Intensitas Cahaya

A switch is a device for disconnecting or connecting electricity, usually used on lights. The Informatics Engineering Study Program (PSTI) of the Faculty of Engineering of the University of Mataram (UNRAM) has several classrooms with light switches controlled by manual switches. Problems occur when classroom users do not turn off class lights after use or when the room has sufficient lighting from outside. The solution is by implementing an automatic control system based on Internet of Things (IoT) that uses several sensors as a trigger switch. The monitoring system created can display light intensity data, motion status, and lamp status in real time obtained from the electronic circuit of the system via the MQTT protocol. Based on the test scheme carried out, the system created can perform lamp management based on the conditions received. MOS testing produces value 4.58 from scale 5 shows that the system is feasible to use.

Open source arc analyzer: Multi-sensor monitoring of wire arc additive manufacturing

Low-cost high-resolution metal 3-D printing remains elusive for the scientific community. Low-cost gas metal arc wire (GMAW)-based 3-D printing enables wire arc additive manufacturing (WAAM) for near net shape applications, but has limited resolution due to the complexities of the arcing process. To begin to monitor and thus control these complexities, the initial designs of the open source GMAW 3-D printer have evolved to include current and voltage monitoring. Building on this prior work, in this study, the design, fabrication and use of the open source arc analyzer is described. The arc analyzer is a multi-sensor monitoring system for quantifying the processing during WAAM, which includes voltage, current, sound, light intensity, radio frequency, and temperature data outputs. The open source arc analyzer is tested here on aluminum WAAM by varying wire feed rate and measuring the resultant changes in the sensor data. Visual inspection and microstructural analysis of the printed samples looking for the presence of porosity are used as the physical indicators of quality. The value of the sensors was assessed and the most impactful sensors were found to be the light and radio frequency sensors, which showed arc extinction events and a characteristic “good weld” peak frequency.

SOCIOECONOMIC STATUS FROM SPACE: EXAMPLE OF ESTIMATING THAILAND’s SUB-DISTRICT HOUSEHOLD INCOME BASED ON REMOTELY SENSED AND GEOSPATIAL DATA

Abstract. The socioeconomic data, such as household income, is an important indicator of people’s well-being. However, due to the limited resource in many developing countries such as Thailand, the data obtained from household income surveys are often incomplete. As a result, the annual household survey usually contains a gap at the municipality household level. In this study, we aim to quantify the household income with K-NN imputation models at the sub-district level using satellite imageries and geospatial data as proxies to socioeconomic indicators. We examined the role of satellite and geospatial data in household income estimation, applied the K-NN imputation methods to estimate the missing income data by using various geographical and statistical variables, and quantified how these data improved the accuracy of sub-district household income estimation. Our results illustrated a significant correlation between sub-district household income and geographical data extracted from day-night satellite data, such as night light intensity (r = 0.53), urban density (r = 0.44), residential area (r = 0.68), urban area (r = 0.64), and statistical data as well as household expenditure (r = 0.97). These can be used to improve the socioeconomic indicators’ estimation as well as household income in sub-district level. The income imputation from geographical data perform better result than purely statistical variables. Especially, the night light intensity can infer the wealth of people living in large scale areas, while day-time satellite images can be interpreted for land use and land cover also implying socioeconomic status. Such socioeconomic proxy from space provides spatially explicit information in further study.

Otomatisasi Eksperimen Interferensi Tiga Celah

Automation of three slit interference experiments has been carried out. The light interference is an interesting phenomenon to observe. The observation of the three-slit interference pattern uses a light sensor that is connected to the computer through the interface. Light intensity data will be directly recorded into the computer and displayed in the form of graphs of the light intensity versus time. To measure the pattern of the formed dark light, the light sensor is placed on a linear drive system. This drive system will move the sensor to the left or right to record the intensity of the pattern of dark light. The purposes of this study are: 1) designing an automatic experiment to observe three slit interference patterns and 2) measuring the wavelength of the light source, He-Ne laser, used in the experiment. From the experiment, we find that the wavelength of He-Ne laser is nm.

Variation of leaf morphology of hibiscus rosa-sinensis l. under various light intensities at Universitas Indonesia campus area and Citayam, Depok

Hibiscus rosa-sinensis L. is a plant that has been cultivated as an ornamental plant, especially in Indonesia. Universitas Indonesia, located in Depok, has ten variations of H. rosa-sinensis in size, shape, and color of flowers. The flower shape consists of three types, namely, single, double, and crested. In this study, it is reported the comparison of leaf morphology from several types of H. rosa-sinensis L. Twenty leaves from each variety were used for morphometric measurement, and light intensity data from each location of the plant variety was also collected. There are two locations, Universitas Indonesia (UI) Campus Area and Citayam. The results showed that two individuals Crested Peach plant in Citayam, which grown under different light intensity has significantly different in leaf surface area but no difference in stomata surface area. Big Single Red and Double Pink located in UI exposure by the same light intensity has the same leaf surface area and stomata surface area. Comparing Small Single Red Citayam and Small Single Red UI exposure by different light intensity has significantly different in leaf surface area and stomata surface area. Two Crested Peach in UI, exposured by the same light intensity, were significantly different in leaf surface area and has the same stomata surface area. This study showed that light intensity could influence the variation of leaf morphology of several Hibiscus rosa-sinensis L. flower types, but not all flower types.

Prediction of soil humidity based on random weight Particle Swarm Optimized Extreme Learning Machine

The prediction of high quality soil moisture is of great significance to agricultural production and scientific research. In order to solve the problem that the prediction results of (ELM) regression model of limit learning machine are affected by input parameters, the stochastic weight particle swarm optimization algorithm (RandWPSO) is applied to ELM regression model. In this paper, a soil moisture prediction method of particle swarm optimization limit learning machine based on random inertia weight is proposed. In this method, the data of soil temperature and light intensity measured by sensor are used to preprocess the data, the training sample set is constructed, and the ELM regression model is established. The input weight and threshold in ELM are optimized by using random weight particle swarm optimization algorithm to avoid falling into local optimization, thus the prediction model of soil moisture based on RandWPSO-ELM is established. The soil moisture of sugar beet in Hulan area was studied. The experimental results show that the method has high accuracy and stability, and can provide an effective reference for the growth of sugar beet in greenhouse.

What do we know about poverty in North Korea?

Reliable quantitative information on the North Korean economy is extremely scarce. In particular, reliable income per capita and poverty figures for the country are not available. In this contribution, we provide for the first time estimates of absolute poverty rates in North Korean subnational regions based on the combination of innovative remote-sensed night-time light intensity data (monthly information for built areas) with estimated income distributions. Our results, which are robust to the use of different methods to approximate the income distribution in the country, indicate that the share of persons living in extreme poverty in North Korea may be larger than previously thought. We estimate a poverty rate for the country of around 60% in 2018 and a high volatility in the dynamics of income at the national level in North Korea for the period 2012–2018. Income per capita estimates tend to decline significantly from 2012 to 2015 and present a recovery since 2016. The subnational estimates of income and poverty reveal a change in relative dynamics since the second half of the 2012–2018 period. The first part of the period is dominated by divergent dynamics in income across regions, while the second half reveals convergence in regional income.

PERBANDINGAN KELUARAN PANEL SURYA DENGAN DAN TANPA SISTEM PENJEJAK

Solar power plants are power plants that convert solar energy (light) into electrical energy. Generation of electricity can be done by using photovoltaic or can also called solar cell, which happened at this time, solar cell can not absorb sunlight optimally, because solar cell only silent in one direction (static) therefore needed smart system for generator Solar power for solar power plants to work more optimally, to make the smart system is needed to read data from several sensors. To find the direction of the arrival of the sunlight rays, used four light dependent resistor sensor (LDR). Light intensity data processing, motor rotation direction determination and other sensor data will be done by microcontroller. Then the data residing on the solar power plant will be displayed on the display and measured how much different in voltage, current and power generated by solar panel. Then the output of the solar power plant be compared among the system with tracking and without tracking.

A Multi-Sensor Data Fusion System for Laser Welding Process Monitoring

Most existing laser welding process monitoring (LWPM) technologies focus on detecting post-process defects. However, in sheet metal laser welding applications such as welding of electronic consumer products during mass production, in-process defect detection is more important. In this article, a compact LWPM system using multi-sensor data fusion to detect in-process defects has been built. This system can collect the time series of plasma intensity, light intensity and temperature data for feature analysis. To verify the system's effectiveness, a plasma-light-temperature dataset has been compiled, which consists of 5,836 samples of nine classes, including one positive class and eight negative classes of typical in-process defects. A multi-sensor data fusion network based on a convolution neural network for in-process defect detection, called IDDNet, has also been proposed. Experimental results have demonstrated that IDDNet can achieve better multi-classification results than the support vector machine, with an overall accuracy of 97.57%. In particular, considering this monitoring process as a binary classification problem, IDDNet can achieve a 99.42% accuracy. Moreover, IDDNet can reach an average speed of 0.79ms per sample on a single GTX 1080ti graphics card, which meets the real-time requirement for industrial production. The proposed LWPM system has been successfully verified in real applications of sheet metal laser welding.

Mobile Light Storage: Make the Light Smarter

Abstract This paper explores a low-cost portable visible light communication (VLC) system to support the increasing needs of lightweight mobile applications. VLC grows rapidly in the past decade for many applications (e.g., indoor data transmission, human sensing, and visual MIMO) due to its RF interference immunity and inherent high security. However, most existing VLC systems heavily rely on fixed infrastructures with less adaptability to emerging lightweight mobile applications. This work proposes Light Storage, a portable VLC system takes the advantage of commercial smartphone flashlights as the transmitter and a solar panel equipped with both data reception and energy harvesting modules as the receiver. Light Storage can achieve concurrent data transmission and energy harvesting from the visible light signals. It develops multi-level light intensity data modulation to increase data throughput and integrates the noise reduction functionality to allow portability under various lighting conditions. The system supports synchronization together with adaptive error correction to overcome both the linear and non-linear signal offsets caused by the low time-control ability from the commercial smartphones. Finally, the energy harvesting capability in Light Storage provides sufficient energy support for efficient short range communication. Light Storage is validated in both indoor and outdoor environments and can achieve over 98% data decoding accuracy, demonstrating the potential as an important alternative to support low-cost and portable short range communication.

Desert crossing strategies of migrant songbirds vary between and within species

Each year, billions of songbirds cross large ecological barriers during their migration. Understanding how they perform this incredible task is crucial to predict how global change may threaten the safety of such journeys. Earlier studies based on radar suggested that most songbirds cross deserts in intermittent flights at high altitude, stopping in the desert during the day, while recent tracking with light loggers suggested diurnal prolongation of nocturnal flights and common non-stop flights for some species. We analyzed light intensity and temperature data obtained from geolocation loggers deployed on 130 individuals of ten migratory songbird species, and show that a large variety of strategies for crossing deserts exists between, but also sometimes within species. Diurnal stopover in the desert is a common strategy in autumn, while most species prolonged some nocturnal flights into the day. Non-stop flights over the desert occurred more frequently in spring than in autumn, and more frequently in foliage gleaners. Temperature recordings suggest that songbirds crossed deserts with flight bouts performed at various altitudes according to species and season, along a gradient ranging from low above ground in autumn to probably >2000 m above ground level, and possibly at higher altitude in spring. High-altitude flights are therefore not the general rule for crossing deserts in migrant songbirds. We conclude that a diversity of migration strategies exists for desert crossing among songbirds, with variations between but also within species.

Integrated Multimedia City Data (iMCD): A composite survey and sensing approach to understanding urban living and mobility

We describe the Integrated Multimedia City Data (iMCD), a data platform involving detailed person-level self-reported and sensed information, with additional Internet, remote sensing, crowdsourced and environmental data sources that measure the wider social, economic and physical context of the participant. Selected aspects of the platform, which covers the Glasgow, UK, city-region, are available to other researchers, and allows knowledge discovery on critical urban living themes, for example in transportation, lifelong learning, sustainable behavior, social cohesion, ways of being in a digital age, and other topics. It further allows research into the technological and methodological aspects of emerging forms of urban data. Key highlights of the platform include a multi-topic household and person-level survey; travel and activity diaries; a privacy and personal device sensitivity survey; a rich set of GPS trajectory data; accelerometer, light intensity and other personal environment sensor data from wearable devices; an image data collection at approximately 5-second resolution of participants’ daily lives; multiple forms of text-based and multimedia Internet data; high resolution satellite and LiDAR data; and data from transportation, weather and air quality sensors. We demonstrate the power of the platform in understanding personal behavior and urban patterns by means of three examples: an examination of the links between mobility and literacy/learning using the household survey, a social media analysis of urban activity patterns, and finally, the degree of physical isolation levels using deep learning algorithms on image data. The analysis highlights the importance of purposefully designed multi-construct and multi-instrument data collection approaches that are driven by theoretical frameworks underpinning complex urban challenges, and the need to link to policy frameworks (e.g., Smart Cities, Future Cities, UNESCO Learning Cities agendas) that have the potential to translate data to impactful decision-making.

Design and Research of a Color Discrimination Method for Polycrystalline Silicon Cells Based on Laser Detection System

In this paper, a method of color discrimination based on sample sensitivity to light wavelength is proposed based on the reflection spectra of a large number of samples and the statistical calculation of the measurement data. A laser detection system is designed to realize the color discrimination. For the color discrimination of polycrystalline silicon cells, the most sensitive wavelength, 434 nm, and the least sensitive wavelength, 645 nm, of polycrystalline silicon cells is obtained according to this method. A laser detection system was built to measure the polycrystalline silicon cells. This system consists of two lasers, optical shutters, collimating beam expanding systems, an optical coaxial system, sample platform, collecting lens, and optical power meter or optical sensor. Two laser beams of different wavelengths are beamed coaxially through the optical coaxial system onto a polycrystalline silicon cell and are reflected or scattered. The reflected or scattered lights are collected through a lens with a high number aperture and received separately by the optical power meter. Then the color value of the polycrystalline silicon cell in this system is characterized by the ratio of light intensity data received. The system measured a large number of previous polycrystalline silicon cells to form the different color categories of polycrystalline silicon cells of this system in the computer database. When a new polycrystalline silicon cell is measured, the color discrimination system can automatically classify the new polycrystalline silicon cell to a certain color category in order to achieve color discrimination.

Nutrient Removal from Chinese Coastal Waters by Large-Scale Seaweed Aquaculture Using Artificial Upwelling

Ecological engineering by artificial upwelling for enhancing seaweed growth and consequently increasing nutrient removal from seawater has proved promising in combating intense coastal eutrophication. However, a key issue needs to be answered: how much economic and ecological benefit could this engineering bring if it were to be implemented in national aquaculture areas. This study estimated the promoting effect of nutrient concentration change induced by artificial upwelling on kelp growth using a model simulation based on the temperature, light intensity, and nutrient concentration data from three bays in Shandong Province, China— Aoshan Bay, Jiaozhou Bay, and Sanggou Bay. Our results indicate that ecological engineering by artificial upwelling can increase the average yield of kelp by 55 g per plant. Furthermore, based on the current existing kelp aquaculture area of China and the aquaculture density of 12 plants/m2, we inferred that this ecological engineering could increase the natural kelp yield by 291,956 t and the removal of nitrogen (N) and phosphorus (P) nutrients by 4875–6422 t and 730–1080 t, respectively.

Technology Roadmapping Architecture Based on Knowledge Management: Case Study for Improved Indigenous Coffee Production from Guerrero, Mexico

Having demonstrated its importance for economic and human developments, technological change is considered one of the biggest supports worldwide. Today, with the population increase, the inclusion of technology is considered the most appropriate way to reduce the impact of this challenge. Considering 171 indigenous coffee producers from Paraje Montero and Tierra Colorada from Guerrero, Mexico, the present study proposes technological routes for the indigenous coffee production chain and the inclusion of emerging technologies such as sensors, actuators, and processing devices basing on the requirements of the chain. During face-to-face sessions, questionaries, field visits, and literature review for knowledge management, the results expose the need of effective actions against diseases and the reduction of climate change, lack of infrastructure, old plantations, and lack of commercialization channels; for these and considering the requirement of greenhouse technology by indigenous coffee producers and following the labor value driver of the digital compass, the necessity of several kinds of sensors, technologies, and methodologies has been identified with high possibilities to be implemented by similar producers analyzed in this manuscript to help in solving the problems identified in this work. The combination of remote sensing, signal processing, and spectroscopy could be employed to explore mineralogical features of soil and help problems with fertilization; sensor modules to collect temperature, humidity, and light intensity data are a priority for greenhouse monitoring; electrochemical sensors and optical technologies could be of great help to detect the presence of diseases in coffee plants; and the installation of a greenhouse solar dryer is necessary to reduce the time of the sun drying process and protect the coffee cherry. These emerging technologies will help to improve the production of coffee. The study contributes to identify a technology roadmap proposing technological implements according to indigenous coffee production chain requirements and serves as support for future studies in indigenous regions.

Development of light intensity data acquisition system to identify the suitability of soil conservation plants under the stand of Cocoa trees

One of the causes of the decline in cocoa productivity is the decreasing quality of land due to erosion. Application of conservation techniques to cocoa land are limited because this plant is an annual plant. One possible conservation technique is to conserve soil through vegetation. The problem in cultivating plants under tree stands is the lack of sunlight intensity because of the shade of canopy plants and protective plants. To determine the level of cover that is suitable for the growth of conservation plants, self-developed tools have been built to measure intensity of the sun light. The sensor used is the NHGH09BU Photosynthetic Active Radiation Sensor. This sensor connected to the Arduino UNO microcontroller module. The result of the test shows that this system can display a pattern of changes in the intensity of sunlight for 24 hours, where data above 300 W / m2 reached at 10.00-14.30, and 0 W / m2 at 16.50 -7.20.