Design of a Wireless Environment Parameter Measuring Instrument Based on Solar Energy

This research paper explores the world of nearly real time analytics by focusing on methods of combining information obtained from Environmental Sensor data. The study utilized a customized setup consisting of three arrays of sensors connected to Raspberry Pi devices. It. Analyzed a dataset that encompassed various environmental conditions. By utilizing the Random Forest algorithm this research investigated how sensor readings, including temperature, humidity, LPG concentrations, smoke, light intensity and motion detection can be fused together. The methodology used cross-validation to ensure model training while visually presenting the intricate relationships, between environmental parameters. The results demonstrated the performance of the Random Forest model through visualizations showing Out of Bag (OOB) error rates and a comparative analysis of machine learning classifiers. The findings shed light on the potential of combining information from sensors to enable reliable predictions using Environmental Sensor data. This provides a foundation for advancements in analytics and applications related to environmental monitoring.

Light energy management in peach: utilization, photoprotection , photodamage and recovery. Maximizing light absorption in orchard is not always the best solution

The present paper describes the design of an intelligent photosensitive tracker, which is used to improve the efficiency of solar energy conversion by concentrating photovoltaic systems. The photosensitive sensor outputs a real-time signal sampled by multi solar cells. These signals are used to evaluate the light intensity and to realize the tracking function. Two operating modes (photosensitive sensor tracking and timed tracking) and a wake-up function are designed into the system. Four separate photosensitive quadrants cross-collect signals in real time. The system compares these signals and sends control commands using a microcontroller to drive two stepping motors to control the attitude of the solar cells. Based on light intensity detection, the center solar cell controls switching between operating modes. Finally, a system sensitivity test and a comparison test of power generation between a solar cell using this intelligent photosensitive tracker and another fixed facing south at an elevation angle of 45° are conducted. The performance of the cell using the intelligent photosensitive tracker is better, and the converted solar energy is increased by up to 34.77%.

In order to meet the increasing energy demands, renewable energy sources are considered as the most dependable and suitable solution. Solar photovoltaic energy is one of the most potential renewable energy sources available today, with no carbon emissions. Solar energy is generated as a result of the atomic fusion reactions that occur at the sun's core. It represents all electromagnetic radiation (visible light, infrared, ultraviolet, X-rays, and radio waves). Recently, Solar panels are monitored by using an Internet of Things (IoT)-based system to gather and evaluate solar energy characteristics in order to ensure a reliable power output and performance. Based on its ability to evaluate peak performance (photovoltaic), one important advantage of the technology is enhanced solar PV system maintenance. PV monitoring systems intend to provide a low-cost solution by continuously presenting remote energy yields and performance on a computer or smart phone. Environmental conditions such as voltage, current, temperature, light intensity, and dust are measured and recorded by the IoT-based system. Furthermore, the Wireless monitoring system ensures the highest operational dependability of a PV system at a lowest system cost. Solar radiation may be converted into useful power using photovoltaic (PV) devices. The high initial cost is a significant obstacle to the wider adoption of solar energy systems. Monitoring and control systems are becoming more common as a way to optimize PV system performance and extend the usable life of connected equipment. Data collection, display, and archiving are all handled by the IoT system. The system's sophisticated features can also estimate and detect solar panel damage.

This study investigates the intricate relationships between environmental factors and the growth performance of coconut plant (Cocos nucifera) in a rooftop nursery setting in the tropics. Coconut cultivation is of great economic and ecological importance, making it crucial to understand the environmental variables that influence growth. The coconut plant growth data and environmental parameters, including temperature (T), relative humidity (RH), light intensity (LI), height (H), leaf count (L), frond count (F), and stem diameter (D), were examined weekly over an extended period. Correlation analysis revealed interesting insights into the relationships between these variables. exhibited a positive correlation with temperature (r = 0.59 and light intensity (r = 0.35), suggesting that coconut growth is influenced by seasonal changes in temperature and sunlight exposure. Relative humidity showed a strong negative correlation with temperature (r = -0.75, indicating the interplay between these two critical factors. Notably, stem diameter (D) displayed a positive correlation with height (H) (r = 0.72, emphasizing the importance of vertical growth for overall coconut development. The findings underscore the significance of understanding how these environmental factors interact to influence coconut growth. The positive correlations between temperature, light intensity, and growth parameters highlight the need for optimal climate conditions in rooftop nurseries. Effective environmental management practices, such as shading to mitigate excessive light exposure and maintaining appropriate temperature and humidity levels, are essential for fostering healthy coconut growth.

In this paper, the topological structure of the vehicle wireless network M2M (Machine to Machine) is used as the experimental research model, and four kinds of light coefficients are set as factors affecting the experimental results, namely, light intensity factor ∈ and α, to represent the light intensity coefficient and influence factor. The remaining energy consumption of mobile terminal equipment was measured respectively, the distance parameter from device to device, the maximum transmission energy consumption, and the correlation coefficient between environmental parameters and energy consumption parameters was analyzed. This paper discusses the impact of different topological structures on the environment, energy saving and emission reduction in the relatively flat terrain area, based on the planning scheme of parking area within the coverage range of base station signal, the transmission capability of vehicles as mobile device nodes within the coverage range of base station signal, and the signal coverage range of base station under different light intensity. As the distance between the base station and the vehicle mobile device node changes, the maximum transmission energy consumption of the mobile device node is obtained. Based on the above factors, the optimal performance optimization parking scheme and the optimal energy consumption optimization transmission scheme are obtained.

Integrating STEM (Science, Technology, Engineering, and Mathematics) Education into Solar Energy Curricula as a Key Strategy for Enhancing Students' Interaction and Understanding of Solar Energy Technologies. STEM education can be considered a key strategy for integrating solar energy studies into academic curricula to enhance students' interaction and comprehension of solar energy technologies. This approach not only fosters critical thinking and problem-solving skills but also prepares students for future careers in sustainable energy. The objective of this study is to evaluate the effectiveness of implementing STEM methods in solar energy education. The efficiency of STEM education in solar energy can be assessed through various criteria, including curriculum development,pedagogical strategies, and environmental awareness. As part of this study, scientific research related to this topic and STEM projects based on alternative energy sources were analyzed. A pedagogical experiment was conducted within the physics education curriculum for the course "Alternative Energy Sources." A total of 51 students participated in the experiment. The learning process utilized an educational-scientific stand designed to study the physical characteristics of solar energy converters, Vernier sensors for data collection, and the Vernier Graphical Analysis program to analyze the relationship between solar panel performance and light intensity. Quantitative data were analyzed using mathematical-statistical methods in the JASP software to observe the correlation between the frequency of STEM product usage and exam scores. The Pearson correlation coefficient was found to be r = 0.575, indicating a positive correlation, with p < 0.001, confirming statistical significance. Linear regression analysis yielded a value of R² = 0.331, suggesting that the use of STEM products explains approximately 33% of the variation in exam scores. The study results confirm that the use of STEM-based educational tools focused on solar energy positively impacts students' academic performance. The findings highlight the significance of incorporating STEM approaches into solar energy education programs, contributing to the training of highly qualified specialists in the field of renewable energy. This research can serve as a foundation for the implementation of innovative technologies in the education system.

An investigation on the relationship between the number of Barn Swallow (Hirundo rustica) and environmental parameters in Jelebu, Peninsular Malaysia

Incident Angle and Light Intensity Variation: a Comparative Impact Study on Perovskite, Dye-sensitized and Silicon Heterojunction Solar Cells Towards Building-Integrated Applications

In this study, moisture contents and product quality of Pu‐erh tea were predicted with deep learning‐based methods. Images were captured continuously in the sun‐drying process. Environmental parameters (EP) of air humidity, air temperature, global radiation, wind speed, and ultraviolet radiation were collected with a portable meteorological station. Sensory scores of aroma, flavor, liquor color, residue, and total scores were given by a trained panel. Convolutional neural network (CNN) and gated recurrent unit (GRU) models were constructed based on image information and EP, which were selected in advance using the neighborhood component analysis (NCA) algorithm. The evolved models based on deep‐learning methods achieved satisfactory results, with RMSE of 0.4332, 0.2669, 0.7508 (also with R2 of .9997, .9882, .9986, with RPD of 53.5894, 13.1646, 26.3513) for moisture contents prediction in each batch of tea, tea at different sampling periods, the overall samples, respectively; and with RMSE of 0.291, 0.2815, 0.162, 0.1574, 0.3931 (also with R2 of .9688, .9772, .9752, .9741, .8906, with RPD of 5.6073, 6.5912, 6.352, 6.1428, 4.0045) for final quality prediction of aroma, flavor, liquor color, residue, total score, respectively. By analyzing and comparing the RMSE values, the most significant environmental parameters (EP) were selected. The proposed combinations of different EP can also provide a valuable reference in the development of a new sun‐drying system.

One of the marine commodities, Lobster (Panulirus spp.), has unabated demand in the global market, while, Lobster production remains static due to the difficulty of implementing its rearing activities. Relative rearing of lobster (Panulirus spp.) is usually performed using the floating net cage method with calm water conditions. In contrast, areas with extreme weather conditions tend to have difficulty applying this method. The potential of using the fixed cage method was assessed by rearing the Lobster at Pesona Bahari Banyuwangi Fish Cultivation Group. This research aimed to investigate the feasibility of the environmental conditions in the waters of GWD, Banyuwangi. The study was conducted for three months. Data such as temperature and light intensity through the help of a pendant was collected. Water quality parameters were recorded during this study, including salinity, pH, dissolved oxygen, and current velocity. Sampling was conducted four times to see the relationship between length and weight. The results showed that the GWD environmental parameters were very supportive for lobster rearing, with temperature values ​​ranging from 27.2oC - 30.1oC, DO around 4.6 mg/l - 5.2 mg/l, salinity 28o/oo - 30o/oo, pH 7 - 8.2, the current speed is 0.468 m/s, and the light intensity is 0 lux - 3,616 lux. The growth pattern of all sampling results except sampling 2 (isometric) has a negative allometric result, with length and weight having a solid relationship. The fixed cage method is considered suitable for lobster rearing activities because the environmental parameters follow their natural habitat and the Fulton condition factor (K) value of more than 1. The greater the value of the Fulton condition factor (K), the healthier the condition lobster.

Walang sangit (Leptocorisa oratorius Fabricus) merupakan merupakan salah satu hama penting tanaman padi. Informasi mengenai pola aktivitas harian L. oratorius masih belum banyak diketahui. Penelitian ini bertujuan untuk mengetahui periodisititas harian dan pola aktivitas harian dari L. oratorius pada berbagai ketinggian di wilayah Daerah Istimewa Yogyakarta. Penelitian dilakukan dengan melakukan penghitungan individu L. oratorius di sawah yang memasuki fase generatif setiap jam dari pukul 06.00 sampai pukul 18.00 WIB di ketinggian 40 m dpl (Trirenggo, Bantul), 130 m dpl (Seyegan dan Mlati, Sleman), dan 340 m dpl (Ngemplak dan Pakem, Sleman). Pengukuran parameter lingkungan (suhu udara, intensitas cahaya, dan kelembaban udara) juga dilakukan di setiap sawah yang diobservasi setiap 15 menit untuk rentang waktu yang sama. Analisis data dilakukan untuk memperoleh hubungan antara parameter lingkungan dan keberadaan L. oratorius. Analisis data menggunakan korelasi. Secara umum, periodisitas harian L. oratorius memiliki dua puncak (pukul 06.00–07.00 WIB dan 16.00–17.00 WIB) dan lembah (pukul 11.00–12.00 WIB). Aktivitas yang umum ditemukan sepanjang waktu adalah makan dan berkunjung. Aktivitas kawin terjadi pada pagi hari dan aktivitas berteduh pada siang hari. Faktor suhu udara dan intensitas cahaya menunjukkan korelasi negatif, sedangkan faktor kelembaban menunjukkan korelasi positif. Pada ketinggian yang berbeda, tidak ditemukan perbedaan signifikan, baik periodisitas, pola aktivitas, dan parameter lingkungan, kecuali pada ekosistem sawah pada ketinggian 130 m dpl.

In order to improve the automation of indoor flower environment monitoring, enable the flowers grow in the best environment, this paper designs an automatic control system of temperature, humidity and illumination based on STC89C52 single chip microcomputer. Temperature sensor DS18B20 is applied to sense indoor air temperature, meantime, YL-69 soil moisture sensor and photosensitive resistance are used to sense soil relative humidity and light intensity respectively. Temperature, humidity and light intensity are transmitted to single chip microcomputer for analysis and processing, and the results are displayed by OLED display module. The upper and lower limits of environmental parameters are manually preset through the keyboard. When the temperature and light intensity exceed the upper limit, the system can send out alarm signals and output control signals to drive the corresponding actuator to work; when the soil moisture is lower than the lower limit, the system will automatically alarm and water automatically; when the humidity reaches the upper limit, watering will be stopped to ensure the indoor environmental parameters in the best value suitable for flower growth. The system has been tested and debugged. The results show that the control system can effectively process and display the flower environment information, achieving the purpose of automatically adjusting and controlling the temperature, humidity and illumination of flowers, has strong promotion value.

Performance-based design of environmental parameters for offshore wind turbine foundations

Energy efficiency in cellular networks is a growing concern for cellular operators with regard to maintaining profitability and reducing their overall environmental impact. Because evolved node Bs (eNBs) for long-term evolution wireless cellular networks are deployed to accommodate peak traffic, they are underutilized most of the time, especially under low-traffic conditions. Hence, switching eNBs on and off in accordance with traffic pattern variations is considered to be an effective method of improving energy efficiency in cellular networks. However, two main concerns of network operators when applying this technique are coverage issues and securing radio service for an entire area in response to the increased size of some cells to provide coverage for cell areas that are switched off. This study focuses on the parameters that affect coverage in order to find a balance between cellular network energy consumption and the area of cell coverage. To achieve this goal, particle swarm optimization, a bio-inspired computational method, has been adopted in this study to maximize the cell coverage area under the constraints of the transmission power of the eNB $$(P_{tx})$$(Ptx), the total antenna gain (G), the bandwidth (BW), the signal-to-interference-plus-noise ratio (SINR), and shadow fading $$(\sigma )$$(�). In addition, the study investigated potential for gains in operational expenditures by operating eNB on solar energy. The optimum criteria, including economic, technical and environmental feasibility parameters, were analyzed using the HOMER.