As the foundation of today's digital infrastructure, cloud computing is boosting demand for data
centers. However, the rapid expansion of cloud services has resulted in high energy usage, raising worries
about the environment. The incorporation of renewable energy sources into cloud data centers is examined in
this research as a viable strategy to lessen the environmental effect. We examine the obstacles, prospects, and
optimal approaches for integrating renewable energy into data centers, providing a route map for attaining
carbon neutrality in cloud computing.

AIoT—the agricultural Internet of things—represents a revolutionary approach to contemporary farming by combining artificial intelligence (AI) and the Internet of things (IoT). This study examines the benefits of combining AI with IoT, with particular attention to how these technologies might be used in resource management, livestock tracking, and precision farming. In order to enable real-time data analysis and decision-making, the article explores the technological developments and techniques that underpin AIoT, including machine learning algorithms, neural networks, and edge computing. Increased crop yields, better resource management, and enhanced animal welfare are all made possible by the significant gains in efficiency, productivity, and sustainability that follow. The study illustrates how AIoT solutions are transforming agriculture through case studies from different locations and comparative analysis, offering concrete proof of reduced environmental impact and increased operational efficiency. The paper highlights the ecological and economic advantages of AIoT in farming through a thorough examination backed by data-driven insights.

Minimum cost spanning tree and shortest path algorithms are fundamental components of
artificial intelligence, enabling the optimization of various processes. They find applications
in network design, autonomous vehicle route planning, robotics, telecommunications, supply
chain logistics, and game development. These algorithms play a crucial role in cost-efficient
infrastructure creation, real-time navigation, obstacle avoidance, data routing, supply chain
optimization, and realistic NPC behaviour, enhancing efficiency and decision-making across
AI applications.

Neural networks are a class of machine learning models inspired by the structure and functioning of
the human brain. These models consist of interconnected nodes, often referred to as neurons or
artificial neurons, organized in layers. This comprehensive review explores the evolutionary
landscape of neural networks, tracing their transformative journey from foundational perceptrons to
the forefront of deep learning. The paper provides a detailed examination of the architectures,
methodologies, and breakthroughs that have defined the progression of neural networks. Special
emphasis is placed on the impact of deep learning, unraveling the complexities of contemporary
models. The review encompasses a historical perspective, highlighting pivotal milestones and
innovations that have propelled neural networks into prominence. In addition, the paper addresses
the practical applications and implications of these advancements across various domains, including
computer vision, natural language processing, and reinforcement learning. The challenges and
limitations inherent in the development of neural networks are scrutinized, offering a balanced
perspective on their capabilities. Furthermore, the review elucidates the ongoing research directions,
such as explainable AI and transfer learning, shaping the future trajectory of neural network
development. Through a synthesis of theoretical foundations and practical considerations, this paper
serves as a valuable resource for researchers, practitioners, and enthusiasts seeking a profound
understanding of the intricate evolution of neural networks in the realm of artificial intelligence.

The recently proposed LoRa low power wide area network (LPWAN) technology is discussed and
analyzed. First of all, performance metrics of a single LoRaWAN end device has been analyzed, namely uplink
throughput and data transmission time. Then illustrative application scenario with the maximum number of end devices
which can be served by a single LoRaWAN base station has been analyzed and the spatial distribution of these devices is
discussed. The LoRa endpoints are the elements of the LoRa network where the sensing or control is undertaken. They
are normally located remotely and battery operated. They can be setup to communicate with a LoRa Gateway. The end
node comprises of a sensor, microprocessor and a LoRa transceiver. The gateway can receive from any LoRa device and
is designed to be fully customizable for a targeted application with post-processing features based on high-level
languages. It receives the transmitted data from the end devices.
KEYWORDS: LoRa, LPWAN, LoRaWAN

Although artificial intelligence is the basis of innovation, it currently affects the
banking sector. Improve customer service, credit risk assessment, asset management,
criminal investigation and compliance processes. Artificial intelligence helps many
departments through decision making, automating processes and streamlining tasks.
As a result, banks experience better profits, lower costs, better customer service and
better decisions. Although these results exceed the limits of intelligence, they still
need to be taken into account. These may be the high cost of AI, the potential for
errors, and the need for technical expertise. Specific advantages and disadvantages
depend on how AI is used.

This paper explores the mixing of IOT-pushed pc imaginative and prescient technology within
smart transportation programs. By leveraging the capabilities of Internet of Things (IOT) devices and
advanced laptop imaginative and prescient algorithms, sizable improvements can be completed in
diverse elements of transportation structures. The paper discusses the capacity of this technology in
traffic control, automobile monitoring, public protection, pedestrian protection, smart parking, visitors
violation detection, road circumstance monitoring, public delivery optimization, environmental
monitoring, and driver help systems. Through real-time statistics series, evaluation, and intelligent
choice-making, IOT-driven laptop imaginative and prescient solutions promise to decorate efficiency,
safety, and sustainability in urban transportation networks. This summary affords a concise evaluate of
the possibilities and blessings provided by way of the integration of IOT and laptop vision technologies
in clever transportation packages.
KEYWORDS: Public Protection, Pedestrian Protection, Smart Parking, Visitors Violation Detection

ABSTRACT
The broad objective of this study is the attacks, threats and vulnerabilities of cyber infrastructure, which includes hardware and software systems, networks, enterprise networks, intranets, and its use Cyber Intrusion. To achieve this objective, the paper attempts to explain the importance of the network intrusion and cyber theft. It also discusses, in vivid detail, the reasons for the accelerated spread of Cyber crimes. The paper also includes full description and definition of cyber security, its role Network intrusion and cyber identity theft plays in, reasons for the increase in discussion Cyber crimes and their impact. In closing the authors recommend some preventive measures and possible solutions to cyber security attacks, threats and vulnerabilities. The paper concludes that technology has a role to play in mitigating the impact of cyber attacks, the vulnerability remains with human behavior and psychological tendencies.

A Study on Attack, Threats, Vulnerability

Abstract:
The broad objective of this study is the attacks, threats and vulnerabilities
of cyber infrastructure, which includes hardware and software systems,
networks, enterprise networks, intranets, and its use Cyber Intrusion. To
achieve this objective, the paper attempts to explain the importance of G
in the network intrusion and cyber theft. It also discusses, in vivid detail,
the reasons for the accelerated spread of Cyber crimes. The paper also
includes full description and definition of cyber security, its role Network
intrusion and cyber identity theft plays in, reasons for the increase in
discussion Cyber crimes and their impact. In closing the authors
recommend some preventive measures and Possible solutions to cyber
security attacks, threats and vulnerabilities. The paper concludes that
While technology has a role to play in mitigating the impact of cyber
attacks, the vulnerability remains with human behavior and psychological
tendencies. While the literature supports the threats Psychological
vulnerability to cyber attacks Offers investment in organizational
education campaigns Optimism that cyber attacks can be mitigated.
Keywords: Cyber Attacks, Cyber Vulnerability, Threats, Warfare

Disease Prediction using Machine Learning is the system that is used to predict the diseases from the
symptoms which are given by the patients or any user. The system processes the symptoms provided
by the user as input and gives the output as the probability of the disease. Naïve Bayes classifier is
used in the prediction of the disease which is a supervised machine learning algorithm. The probability of the disease is calculated by the Naïve Bayes algorithm. With an increase in biomedical and healthcare data, accurate analysis of medical data benefits early disease detection and patient care. By using linear regression and decision tree we are predicting diseases like Diabetes, Malaria, Jaundice, Dengue, and Tuberculosis.
Keywords: Disease Prediction, Machine learning, Decision Tree, Random Forest, Naive bayes
algorithm.

Social media platforms have revolutionized the way businesses engage with their customers. Over
the last decade, social networks like Twitter, Facebook, LinkedIn, Instagram, and YouTube have gained remarkable attention. As these platforms have become increasingly affordable and popular, businesses find it convenient to reach their consumers through them. This project aims to identify the role of social media marketing strategy and evaluate its importance over traditional marketing strategy in building brand names and influencing consumer behavior. The study concludes that social media has created a "survival of the fittest" phenomenon among online brands and products, and the increase in e-commerce will contribute to economic growth.
Keywords – Social Media, E-Commerce, Digital Marketing.