VOLUME 12, ISSUE 6, JUNE 2024

Abstract: The adoption of hexacopter drones for fertilizer spraying in agriculture signifies a major leap forward in precision farming techniques. These drones, with their distinctive six-rotor setup, offer enhanced stability and greater payload capacity, essential for the precise and efficient application of fertilizers. This study explores the use of hexacopter drones outfitted with advanced GPS and sensor systems to deliver fertilizers accurately, thus optimizing usage and minimizing environmental harm. Hexacopters' ability to traverse difficult terrains and swiftly cover extensive fields results in considerable labor and time savings compared to traditional methods. However, the widespread use of this technology faces obstacles such as high initial investment costs, regulatory compliance issues, and the need for specialized training. This paper provides a detailed analysis of the technical specifications, benefits, challenges, and future prospects of using hexacopter drones for fertilizer spraying, highlighting their potential to improve agricultural productivity and sustainability.

Abstract: Fire outbreak is the common issue happening everywhere and the damage caused by this type of incidents is tremendous towards nature and human. Vision based fire detection system have recently gained popularity as compared to traditional sensor-based fire detection system. However, the detection process by image processing technique is very tedious.

We proposed a fire detection algorithm using Convolutional Neural Networks (CNN) to achieve high-accuracy fire image detection, trained on a dataset consisting of 3696 fire and 541 non-fire images, totaling 4237 images. Out of these, 2857 images were used for training and 1921 for testing. The model employs convolution, activation functions, and max pooling operations. Through experimentation with different batch sizes and epoch values, we achieved a model accuracy of 94%, correctly predicting 1817 out of 1921 test images.

Our study also reviews smoke and fire detection techniques, emphasizing early detection's importance. We discuss various methods, including RGB and HSI models, aiming to minimize false alarms through optimized technologies.

Furthermore, we address human-animal conflicts in forest zones by developing a monitoring system using cameras to detect intrusions, classify them, and notify relevant authorities.

Abstract: The energy requirement in the present world has been hastily boosted in the last few decades and meeting the demands in the current situation has become a great challenge among developing countries, especially a developing country like India habituating world most of the population. When the country's standard of living rises, economic expansion, and industrialisation it becomes more crucial to explore other possible ways for the generation of the power to synchronize the pace. This study aims to review some of the techniques using waste-to-energy which can be used as an alternative to electricity generation. Waste-to-energy can be turned into one of the most sustainable and efficient methods of managing waste while simultaneously generating clean and renewable energy. The incineration technique is one of the most used techniques across the globe. The WtE concept is a ground-breaking strategy that has the potential to lessen human environmental impact. The waste substances are converted into energy at the WtE facility using a heating panel. The electricity created by the WtE plant may be utilized to power homes, companies, and other organizations, lowering the demand for traditional non-renewable electricity. The WtE facility also contributes to a reduction in the quantity of trash transferred to landfills. The WtE plant would minimize the quantity of greenhouse gases like CO2, CO, SO2, NO2, and heavy metals like mercury discharged into the environment by lowering the amount of garbage transported to landfills. Furthermore, the WtE facility would be able to minimise the amount of energy required to transport trash to and from landfills.

Abstract: Shrinkage cracking remains a significant concern in concrete structures, compromising their durability and serviceability. This paper offers a comprehensive examination of shrinkage cracking mechanisms in concrete structures reinforced with synthetic fibers, aiming to provide insights into effective mitigation strategies. The introduction outlines the detrimental effects of shrinkage-induced cracking on concrete structures, including reduced durability, aesthetic concerns, and potential structural vulnerabilities. The need for innovative solutions to address this issue is emphasized, setting the stage for the exploration of synthetic fiber reinforcement. The paper reviews various types of synthetic fibers commonly used in concrete reinforcement, including polypropylene, polyethylene, and nylon fibers, among others. Each fiber type's mechanical properties, such as tensile strength, modulus of elasticity, and aspect ratio, are discussed in relation to their effectiveness in mitigating shrinkage cracking. The mechanisms by which synthetic fibers influence the shrinkage behavior of concrete are elucidated, encompassing aspects such as fiber-matrix interactions, crack bridging, and residual stress redistribution. Experimental studies and field applications are analyzed to assess the effectiveness of synthetic fibers in controlling shrinkage cracking under different environmental and loading conditions. Furthermore, the paper examines key factors influencing the performance of synthetic fibers in mitigating shrinkage cracking, including fiber dosage, aspect ratio, distribution, and compatibility with concrete mixtures. Practical recommendations for optimizing fiber-reinforced concrete mix designs are provided based on empirical data and best practices.

Abstract: Navigation of an object is widely used for target detection. In such systems the nearest objects are detected by distance measurement. The distance measured and choice of sensor depends on type of application and also surrounding environmental issues like temperature, humidity, fog etc. For short distance measurement ultrasonic sensor is used. The ultrasonic sensor output is used to measure the distance. The computation, processing, control and display units are implemented on FPGA. The Xilinx synthesis tool is used for implementing the design on FPGA. FPGAs have faster processing capability, low power consumption and are easily reconfigurable for the necessary applications. The measured distance is displayed on segment displays.

Keywords: FPGA Kit, Ultrasonic sensor HC-SR04, 7-Segment display unit, Xilinx ISE design suit.

Abstract: The "Smart Power Monitoring System using IoT" constitutes a pioneering solution poised to revolutionize the landscape of power management in both residential and industrial settings. Anchored by the ESP8266 NODE MCU microcontroller, this system seamlessly integrates an array of state-of-the-art sensors and modules, all working in concert to deliver real-time monitoring and controlling capabilities. The predominant objective of this innovative system is multifaceted: to elevate energy efficiency, bolster security measures and enable remote monitoring through the dynamic fabric of the IoT. The ESP8266 NODE MCU, functioning as the system's central hub, orchestrates a symphony of components, including a current sensor for precise power consumption insights and a PIR sensor to intelligently detect human motion for enhanced automation. The inclusion of a GSM module ensures timely communication of critical alerts to users via SMS, underscoring the system's responsiveness. Additionally, a relay module facilitates the remote control of appliances, promoting user-friendly power management. A half horsepower induction motor acts as a tangible load indicator, providing users with a visual representation of power fluctuations. The system, powered by a stable 9V 1 Amp DC supply, culminates its capabilities by leveraging the “ThingSpeak” platform to graphically display power consumption trends, empowering users to make informed decisions for sustainable and efficient energy practices. In essence, the "Smart Power Monitoring System using IoT" emerges as a comprehensive and forward-thinking solution, poised to redefine the paradigm of intelligent power management.

Keywords: IoT technology, real-time monitoring, energy consumption analysis.

Abstract: The purpose of the study is to determine the Basic biological functional capacities of Cricket and Football Players. Basic biological functional capacities functions measure through Breath Holding capacity ( (Both Inhalation and Exhalation) and Systolic and Diastolic Blood Pressure. Total , 300 Cricket and 300 Football players from Maharashtra participated in the study and their age ranged between 18-28 years who were regular participation in cricket and football tournaments .The blood pressure were measure through BP Monitor of Amron

The finding reveals that there was in No sig.(significant) difference was found in BHC (Inhale) cricket and Footballers. The finding reveals that there was in sig.(significant) difference was found in BHC (Exhale) cricket and Footballers. The finding reveals that there was No sig.(significant) difference was found in BP (Diastolic) cricket and Footballers. The finding reveals that there was in No sig.(significant) difference was found in B. P(systolic) cricket and Footballers.

Keywords: BHC (Inhale), BHC (Exhale),Football, Cricket

Abstract: This study presents an exploratory data analysis (EDA) and visualization of a vehicle dataset to detect patterns and insights that can inform vehicle performance and trends. We used Python and data analysis libraries like Pandas, Matplotlib, and Scikit-learn to analyse a sample of 1000 rows from the vehicle-1.csv dataset. Our analysis included cleaning, preprocessing, and visualizing the data to identify crucial characteristics and correlations within the dataset.Our findings show significant trends in vehicle attributes and their relationships, providing valuable insights for stakeholders in the automotive industry. Through detailed visualizations, we show how EDA can contribute to understand complex datasets and help data-driven decision-making. This study highlights the significance of thorough data analysis in vehicle data management and sets the stage for future research and applications in predictive analytics and machine learning.

Keywords: Data visualisation, data analysis, Exploratory data analysis, preprocessing.

Abstract: The very initial phase to alleviating losses in the quality and productivity of agricultural products is recognizing plant diseases. Utilizing these modern innovations is a key objective of this effort, which focuses on plant disease detection specifically. The system will use state-of-the-art image processing algorithms to evaluate plant pictures in order to accurately detect diseases and provide suggestions. for the necessary nutrient supplements and pesticides. The suggested technique will not only detect the presence of diseases but will additionally pinpoint specific nutrient deficiencies that have caused issues with crop health. In the end, this will support prompt and effective management of crop diseases, increase agricultural productivity, and lessen financial losses. Equipped with 13505 photos of crop leaves from an available dataset, a Residual Network (ResNet-9) was trained to deal with this classification operation. The postulated ResNet-9 model showcased its viability by achieving 99.20% accuracy on a test set. All in all, employing an open-picture dataset to train ResNet models proposes a reliable path toward crop disease detection.

Abstract: Electricity is an essential source of energy for modern life, and High Voltage Direct Current (HVDC) & Flexible AC Transmission Systems (FACTS) represent advanced technologies that are shaping the new age electrical power transmission & distribution. The benefits of HVDC technology over its HVAC counterpart in long-distance and high-capacity power transmission are obvious, as it offers lower transmission losses, increased stability and possibility to interconnect systems operating on different frequencies. HVDC helps to reduce these energy losses by changing AC to DC before sending it long distances, switching it back to AC and only converting the power once, for example when receiving power from remote renewable energy sources. In general, Flexible AC Transmission Systems (FACTS) are utilized to reduce power losses, increase the loading of transmission lines so that it will provide more security and control gives makes the system flexible. The FACTS devices for the AC systems enhance control and damp out power quality issues, to level of optimization in the performance of an existing system such as Static VAR Compensators (SVC), the Unified Power Flow Controllers (UPFC). AC/DC hybrid technologies: These are the key to controlling power flow, maintaining voltage stability and increasing AC network transmission capacity substantially without major new transmission lines. In the absence of it, HVDC and FACTS works together to meet growing needs for reliable, efficient and sustainable energy transmission. They support the integration of renewable energies, provide benefits for grid stabilisation and facilitate security of supply thanks to a networked configuration of resilient controls. This article presents the benefits, application and impact of HVDC & FACTS technology on global power transmission view..

Keywords: Power Transmission, AC Transmission, Flexible AC. HVDC Tech, Power Flow, Advanced Tech, Network