Climate change poses major challenges around the world, with developing countries particularly vulnerable due to lack of resources and services. Green technologies—such as renewable energy, sustainable agriculture, and green materials—offer promising solutions to mitigate climate change impacts but the adoption of these technologies in developing countries are still uneven, driven by political, economic, and technological factors. This study seeks to examine the role of green technologies in climate change mitigation in four developing countries—India, Brazil, South Africa, and Kenya—through comparative analysis. The problem statement focuses on the inequitable adoption of green technologies in developing countries, where financial constraints, lack of technical expertise, and inconsistent government policies prevent widespread implementation And as a result comes to be considered which shows that green technologies have contributed significantly in reducing carbon emissions in these countries. For example, India’s solar power system installed 62 GW of solar capacity, reducing emissions by 150 million metric tons per year. Brazil’s biofuel industry, which produces 35 billion liters of ethanol a year, has reduced its reliance on fossil fuels for transportation. The Kenya geothermal sector generated 863 MW of electricity, reducing the country’s dependence on fossil fuels by 45%. However, the study also highlights barriers such as inadequate funding, inadequate infrastructure and social opposition, which limit the potential of all these technologies.

The global shortage of donor liver transplants poses a significant challenge to healthcare systems, with thousands of patients dying each year while on waiting lists This study examines the potential of technological liver transplantation 3D bioprinting and advanced stem cell technologies serve as solutions to address this important issue The goal was to create functional liver tissues that are complex structures of the natural liver and some of the important functions, and assess its viability as an alternative organ donor includes hepatocytes and other liver-specific cell types with an optimal pro-mesenchymal differentiation pattern stem cells ( MSCs). Research results showed that these compounds are capable of important liver functions such as liver function, urea excretion, pharmacokinetics, in vitro and in vivo conditions in addition to promising discovery together with early testing in animal models as a viable alternative that represents an important step towards biosynthetic implants.

Blockchain innovation has picked up expanding consideration from investigating and industry over the later a long time. It permits actualizing in its environment the smart-contracts innovation which is utilized to robotize and execute deals between clients. Blockchain is proposed nowadays as the unused specialized foundation for a few sorts of IT applications. Blockchain would aid avoid the duplication of information because it right now does with Bitcoin and other cryptocurrencies. Since of the numerous hundreds of thousands of servers putting away the Bitcoin record, it’s impossible to assault and alter. An aggressor would need to change the record of 51 percent of all the servers, at the precise same time. The budgetary fetched of such an assault would distantly exceed the potential picks up. The same cannot be said for our private data that lives on single servers possessed by Google and Amazon. In this paper, we outline major Blockchain technology that based as solutions for IOT security. We survey and categorize prevalent security issues with respect to IoT data privacy, in expansion to conventions utilized for organizing, communication, and administration. We diagram security necessities for IoT together with the existing scenarios for using blockchain in IoT applications.

The development of high-efficiency photovoltaic systems is essential to prevent environmental pollution, especially in water and air purification. This study addresses the problem of poor performance of existing photocatalytic materials under visible light, which limits their practical application. The main objective of this research was to design and characterize advanced fluorescent materials, enhance their performance by doping composites, and test their performance on the degradation of various impurities Nitrogen-doped TiO2 obtained 90% degradation of methylene blue in 60 minutes in visible light, while undoped TiO2 degradation was 70%. Similarly, the ZnO-based photocatalysts showed 85% removal of pesticides in sunlight, and the TiO2/graphene composites showed 85% reduction of benzene (VOCs) in 2 hours, which exceeded 60 % decrease by pure TiO2 this result highlights the effectiveness of doping and composite fabrication to enhance the photocatalytic performance. The review also highlights the potential for large-scale environmental applications, and the importance of addressing practical challenges such as photocatalyst recovery and energy stability Future research will focus on strategies a through optimization, exploration of new combinations, and long-term field surveys.

Precision agriculture relies heavily on wireless sensor networks (WSNs) to monitor environmental conditions and manage resources efficiently. However, traditional WSN algorithms face significant challenges in energy management, resulting in frequent battery replacements, high maintenance costs, and reduced network reliability. Additionally, issues with high data latency and short network lifetimes hinder real-time decision-making and continuous monitoring. This study aims to address these challenges by developing energy-efficient algorithms that enhance the performance and longevity of WSNs in precision agriculture. The objectives include creating adaptive sampling, dynamic power management, and sleep scheduling algorithms to optimize energy consumption; improving data transmission efficiency and reducing latency through advanced data aggregation techniques; and extending network lifetime with balanced energy load distribution and efficient power usage strategies. The study introduces innovative algorithms that significantly reduce energy consumption and extend network lifetime, contributing to the field with adaptive and dynamic methodologies. Extensive simulations demonstrate that the proposed algorithms achieve a 30% reduction in energy consumption, a 20% decrease in data latency, and a 40% increase in network lifetime compared to traditional methods. Additionally, the packet delivery ratio improved by 10%, and computational overhead was reduced by 30%, highlighting the efficiency and reliability of the proposed solutions. These results are consistent with recent advancements in WSN optimization techniques, such as those utilizing cognitive radio and deep learning, validating the potential of the proposed algorithms for real-world application.

Photovoltaic (PV) panel has received attention due to its environmental advantages; however, It has yet to achieve the desired efficiency and economic maturity. In this regard, PV tracking techniques play a pivotal role in maximizing the performance of the PV system. The main objective of this paper is to determine the optimal scenario for obtaining the highest efficiency and profitability for a rural household in Africa. The tracking options include fixed-tilt (FT), horizontal axis (HM), vertical axis (HV), and dual-axis tracker (DA) using to discover the lowest cost between LF and CC dispatch strategies. The optimal solution according to the lowest net present cost (NPC) as an optimization indicator is identified, and then sensitivity analysis is conducted to generalize the results for other technical, economic, and climate conditions. The FT-based solution indicates the profitable option with NPC, levelized energy cost (LCOE), and CO₂ emissions of $13.7k, $0.258/kWh, and 281.11 kg/year, respectively. The increase in SOC_min values would escalate reliance on the DG to meet the required load, resulting in higher NPC and CO₂ emissions. The highest and lowest increase of NPC by raising fuel price is found under DA and FT trackers, respectively. PV production and the renewable fraction of FT-based and HM-based hybrid systems are more sensitive to changing albedo. Comparison with the previous paper also shows that the optimal HES has $58k and $0.005/kWh lower values of NPC and LCOE, respectively, to satisfy the same load demand.