Abstract Now that the world’s most important problems are the lack of fossil fuel reserves, we need to find a solution to preserve non-renewable resources and replace them with other renewable resources such as solar power. The next focus is on the rising level of undesired gases, such as carbon dioxide, etc. There is a need to regulate the impact of such greenhouse gases. This paper mainly intentional to situate optimal scheduling and to meet the power demand profile by the utilization of available solar energy resources. Considering the above data we have put forth an attempt to scrutinize the leverage of distributed Generation considering solar energy, alone can vary, when associated together they give a dependable wellspring of vitality as a DG is utilized as reinforcement unit for the crisis. So consolidating a solar powered energy source with a diesel generator provides reliable generation, utilizing independent sunlight based renewable power system for a chose area in Vellore region, Tamil Nadu, India. The principle goal of this paper is to decide the optimal sizing dependent on different designs, moreover reduce the cost parameters such as, total net preset Cost (TNPC), system cost of Energy (COE), unmet electric load, CO 2 emissions by utilizing HOMER Software. It is found that the PV/Diesel/converter combination provides optimal results which providing vitality with 0% unmet load at the minimum electricity cost, which is diminished from$ 0.672 to $0.319/Kwh.
All tea plants in India rely on the national grid for their electrical needs and diesel for their thermal energy and transportation, which are encountering high costs, high emissions, and issues of accessibility. In this paper, hybrid renewable systems based on both standalone and grid-connected technologies have been modeled using HOMER Pro software for supplying power to a tea manufacturing plant in a typical rural area in India, namely, Gudalur village (Nilgiris), geographically located at 11°30.2′N and 76°29.5′E, which is presently run by the state grid to meet their energy requirements. The different configurations comprised of Solar PV, biomass, hydro, electrolyzer, boiler, thermal load controller to utilize excess electricity, and waste heat recovery options, and lead-acid batteries were designed to meet 650 kWh/day of electricity for processing units, 101 kWh/day of electricity for general applications, 4,450 kWh/day of thermal energy, and 86.35 kg/day of hydrogen energy. To determine the most feasible system design among various scenarios, several criteria such as NPC, COE, LCOH, and CO 2 emission of the system have been investigated. In the case of off-grid hybrid systems, results show the highest NPC of $7.01 M with an LCOE of $1.06/kWh is obtained for the diesel generator/boiler/reformer/TLC system. It is reduced to $1.75 M with an LCOE of −$.420/kWh for the PV/biomass-CHP/hydro/TLC scenario. In a grid-connected system, the maximum NPC of $6.20 M with an LCOE of $0.835/kWh is obtained for a diesel generator/boiler system, and it is reduced to −$10.5 M with an LCOE of −$.240/kWh for the PV/biomass-CHP/hydro/TLC scenario. Additionally, in the off-grid systems, the PV/biomass-CHP/hydro/TLC system has LCOH of $4.27/kg, which is economical with the highest renewable fraction of 93%. The PV/biomass-CHP/hydro/TLC hybrid system has the lowest LCOH of −$64.5/kg with a maximum renewable fraction of 96% in on-grid systems. The findings show that recovering excess electricity and waste heat would increase renewable fraction, decrease the energy cost and emissions from the system, and emphasize the importance of TLC and CHP in HRES. According to the simulation results, the grid-connected system is more cost-effective than a stand-alone system due to the revenue obtained from selling renewable power to the grid.
In April 2021, during the peak of the second wave of the COVID-19 pandemic in India, hospitals overflowed with COVID-19 patients, and people hesitated to seek necessary care due to fear of contracting the disease. The UDHAVI helpline was set up by a tertiary care hospital in Vellore with the help of district administration, nongovernmental organizations, and various supporting agencies to provide general information, medical advice, counseling, and logistics support to the community.
Methods:
This is a retrospective study of all the phone calls made to the UDHAVI helpline between mid-May and mid-June 2021 during the second wave of the COVID-19 pandemic. The calls were electronically captured as part of the process, and the information was subsequently retrieved and analyzed.
Results:
In all, 677 calls were received. The lines for general information, medical advice, counseling, and logistics support received 168 (25%), 377 (56%), 15 (2%), and 117 (17%) calls, respectively. Home care kits, oxygen concentrators, and food were delivered by volunteers from local nongovernmental organizations and hospitals.
Conclusion:
We believe the details of our experience would be useful in the preparedness and mobilization of resources in the event of any public health emergency. As a result of this initiative, we propose an integrated partnership model for emergency response to any pandemic situation.
Integration of renewable energy systems can provide reliable, environmentally sustainable, and cost-effective alternatives for meeting the demand for electricity in remote locations. In this study, recently developed meta-heuristic techniques are explored to find the optimal design for two combinations of off-grid hybrid renewable energy systems. To evaluate the performance, the Tasmanian devil Optimization (TDO) was compared to three meta-heuristic algorithms, called the COOT bird optimization algorithm (COOT), the Grey wolf algorithm (GWO), and the Beluga whale optimization (BWO), and determined the optimal design of the proposed off-grid energy system in terms of best and worst-case solutions. The system consisting of a solar-battery is more cost-effective, with the lowest total annual cost (TAC) of 36,859 $ and the lowest levelized cost of electricity (LCOE) of 0.0930 $/kWh for 0% LPSPmax level as compared to the wind turbine-battery-diesel generator with the highest TAC (102580 $) and LCOE (0.2589 $/kWh). Hence, a solar-battery hybrid system is more viable for producing clean energy with effective storage and better power system reliability enhancement. Also, the obtained simulation results reveal the supremacy of the TDO compared to the other three meta-heuristic algorithms, where it achieved the optimal solution with a quick convergence time and fewer oscillations.
Tire blow-outs or puncture during the operation of the vehicle is one of the major root causes of road accidents. The drivers lose his/her control of the steering wheel when the tire get punctured or busted leading towards loss of stability of the vehicle causing adverse effects to the vehicle and the passenger. Due to the rapid change in the pressure range within the tyres, the rim of the wheels come in contact with the road surface causing loss of traction and stability of the vehicle leading to accidents. Despite, the rapid advancements witnessed in the field of automobile industry stating from autonomous vehicles to electronic stability unit, a proper solution addressing the issue of accidents caused due to tire blow-outs remains unanswered. In this proposed study, automatic activation of an additional secondary wheel/roller assembly mounted to the chassis using a custom made Zigbee based smart traction system in order to address the traction and stability issues based on the real-time pressure of the tyre is presented. The real-time pressure of the wheels is monitored by the control system which then decides on scheduling the activation of the secondary wheel/roller assembly using a battery operated pneumatic system which will prevent the vehicle from losing its stability. The proposed traction control system consisting of the secondary roller assembly could also be considered as a lifesaving add-on to the passenger vehicle and a replacement for the wheel replacement jack emphasising the market demand of the proposed solution which is a robust and a cost-effective solution.
Abstract: This paper proposes an IoT-based safety system for SAE BAJA All-Terrain Vehicles (ATVs) to improve the safety of riders. The system consists of intelligent safety enhancement system which is integrated with the vehicle to collect data on its location, SOS alert, speed, acceleration, and other important parameters. The collected data is then transmitted to a cloud-based server via wireless communication protocols such as Wi-Fi or cellular network. In this project, we have built an IoT based accident detection with the help of Nodemcu ESP8266 Wi-Fi module and a vibration signal which detect the accidents and send an emergency warning message. The system constitutes of single – board embedded system that has Nodemcu ESP8266 connected to IoT. Nodemcu ESP8266 is an open – source based firmware and development board specially targeted for IoT based applications. The proposed system also includes a remote monitoring and control feature, allowing the rider's friends, family members, or emergency services to track the location and status of the ATV in case of an emergency. Moreover, the system can also be used to monitor the vehicle's maintenance status and provide proactive maintenance recommendations to ensure its optimal performance and longevity. The experimental results demonstrate that the proposed system is effective in enhancing the safety consideration of ATV riders through Blynk – IoT platform and can significantly reduce the risk of accidents through crash alert system. The system can also be easily integrated with other IoT devices and platforms, making it highly scalable and adaptable to different types of vehicles and environments
Palm vein authentication is a highly accurate and secure biometric technology that captures unique vein patterns beneath the palm skin, providing robust authentication. Traditional methods like fingerprint and iris recognition face accuracy and spoofing limitations. Siamese neural networks, designed for pattern recognition, offer promising advancements in biometrics, especially for palm vein authentication. These networks feature two subnetworks extracting and comparing input data to generate a similarity score, enabling precise identification. Siamese networks excel in handling variations in palm position and size, crucial for real-world scenarios. Their adaptability to changing vein patterns over time ensures long-term authentication reliability. Additionally, their low computational requirements make them suitable for mobile integration, facilitating on-the-go authentication. Continuous research and improvements position Siamese neural network-based palm vein authentication as a leading biometric technology, promising unparalleled reliability and security in personal identification. The proposed system provides an accuracy of 98% with EER of 0.25 with PUT Vein dataset.
Energy is an important aspect of a country’s long-term growth, and to meet the increasing electrical demand for reliable manner, there is an urge to plan for future generations. In this study, metaheuristic optimization approaches that have recently been constructed, which include the coati optimization algorithm and hippopotamus optimization, were applied to determine the perfect dimensions for a grid-independent composite renewable energy infrastructure. The optimization problem attempts to reduce the total annual cost of the system while maintaining the reliability of the loss of power supply probability in an acceptable range. Three combinations of hybrid energy systems were designed and optimized, and the optimization findings point out that the system consisting of a photovoltaic module, wind turbine, storage battery, and battery is the most cost-effective optimal energy system. The lowest total annual cost of the PV/WT/SB/DG system obtained by using HOA is $24473, followed by PV/WT/DG at $ 26270 and PV/SB/DG at $35848. Also, the outcomes of the proposed algorithm were contrasted with those of the HOMER platform. When contrasting the effectiveness of optimization methods, the HOA is the optimal solution for resolving the sizing issue since it offers the most effective compromise among robustness, accuracy, and convergence rate.
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