Help Of Cloud Computing Research Articles

IOT Based Smart Grid to Remotely Monitor and Control Renewable Energy Sources using Cloud Computing

Abstract: The growing demand for clean and sustainable energy sources necessitates advancements in grid structure. This project explores the potential of an IOT-based smart grid to remotely monitor and control renewable energy sources. In this, we use solar energy as a renewable energy source, and with the help of cloud computing, we monitor and control different types of loads. The paper highlights the key components, functionalities, and benefits of such a system.The increasing demand for sustainable energy solutions fuels the development of smart grid technologies. This project proposes an IOT (Internet of Things)-enabled smart grid architecture for remote monitoring and control of renewable energy sources. The core concept involves integrating sensors with renewable energy sources like solar or wind turbines. These sensors collect real-time data on energy generation, environmental conditions, and system health. This data is then transmitted over a network to a central control system or a cloud platform for further analysis. By implementing remote control capabilities, grid operators can: regulate energy production based on demand; integrate storage solutions for surplus energy; and improve overall grid stability and reliability. The project concludes by outlining the benefits of this approach, including a reduced carbon footprint, cost savings, and a more sustainable energy future.

Preface

The advent of the fourth information revolution has made the digital economy a major driver of energy transition and low-carbon development. The overall architecture of smart energy is based on intelligence as the core, and based on infrastructure platforms such as intelligent cloud and IoT, as well as AI middle platform, Data middle office ether, etc. And with the help of cloud computing, artificial intelligence, big data, blockchain, digital twins and other technologies, smart energy can promote the intelligent transformation of energy enterprises ultimately.Against such background, the 2023 2nd International Conference on Smart Energy and Electrical Engineering (SEEE 2023) was held via hybrid form during December 22nd to 24th, 2023 in Malaysia. It was attended by about 50 researchers, scientists, engineers, and students working in the fields of smart energy and electrical engineering.The aims of SEEE 2023 are:To create an academic forum for sharing, communication and research at the international level, so that participants can be informed of the latest research directions, contents and results of smart energy and electrical engineering.To provide approaches to the main problems facing smart energy and electrical engineering, creating spaces that encourage discussion and joint development of research, technology development, and innovation.The excellent papers selected form the submissions were approved for presentation at the Conference and publication in this Conference Proceedings. Among the submissions are some submitted from abroad, but are unfortunately not accepted after rigorous review processes.There was an enabling environment for discussion and exchange of ideas, during which topics such as Core Technology of Intelligent Energy Equipment, Smart Transmission and Distribution, Power Grid Dispatching and Automatic Control, Power Systems and Energy, Electrical Theory and New Technology, etc. were presented. Some of the important issues were the sharing and discussion of Wireless Power Transfer and its Application on Electric Vehicle Wireless Charging by Prof. Yiming Zhang (Fuzhou University, China), Corona Loss Characteristics of EHV/UHV AC Transmission Lines by A. Prof. Shilong Huang (North China Electric Power University, China), Integrated Renewable Energy System based on Hydrogen by Prof. Mohan Lal Kolhe (University of Agder, Norway), etc.As in the last meeting, SEEE 2023 was again a space for the integration of undisputed knowledge and sharing of peer experiences within the specific areas of smart energy and electrical engineering. Both conference and presentation sessions were attended by many conference attendees, allowing closer relationships, both academic, as well as scientific and personal. The cordiality and good treatment of the attendees promoted a climate of friendship, which we could enjoy during all the development of the conference agenda.We would like to extend an enthusiastic round of thanks to all our conference authors and speakers for their excellent contributions. We are indebted to the Technical Program Committee for their efforts in making and pushing the conference program. Thanks also to the members of Journal of Physics: Conference Series for making the publication of SEEE 2023’s Proceedings possible.List of Committee Member is available in this pdf.

BloodPatrol: Revolutionizing Blood Cancer Diagnosis - Advanced Real-Time Detection Leveraging Deep Learning & Cloud Technologies.

Cloud computing and Internet of Things (IoT) technologies are gradually becoming the technological changemakers in cancer diagnosis. Blood cancer is an aggressive disease affecting the blood, bone marrow, and lymphatic system, and its early detection is crucial for subsequent treatment. Flow cytometry has been widely studied as a commonly used method for detecting blood cancer. However, the high computation and resource consumption severely limit its practical application, especifically in regions with limited medical and computational resources. In this study, with the help of cloud computing and IoT technologies, we develop a novel blood cancer dynamic monitoring diagnostic model named BloodPatrol based on an intelligent feature weight fusion mechanism. The proposed model is capable of capturing the dual-view importance relationship between cell samples and features, greatly improving prediction accuracy and significantly surpassing previous models. Besides, benefiting from the powerful processing ability of cloud computing, BloodPatrol can run on a distributed network to efficiently process large-scale cell data, which provides immediate and scalable blood cancer diagnostic services. We have also created a cloud diagnostic platform to facilitate access to our work, the latest access link and updates are available at: https://github.com/kkkayle/BloodPatrol.

Exploration on vehicle target detection technology based on wireless networks and its application in intelligent traffic

In the current development of intelligent traffic in many regions, vehicle target detection has always been the focus of attention and research in the field, which can further enhance the overall performance of multiple system modules such as the security module in intelligent traffic system (ITS). This article first analyzed traditional vehicle target detection techniques, which mainly used computer vision (CV) to recognize vehicle targets on the road. However, it was often susceptible to multiple factors such as the environment, and the efficiency and universality of vehicle target detection based on CV were also low. This article also conducted research on vehicle target detection technology based on wireless networks. In this process, both cloud computing and edge computing technologies were used to further improve the efficiency of vehicle target detection based on wireless network, and reduce the use requirements of vehicle target detection. This article selected 100 images to test the accuracy of two vehicle detection technologies that do not combine wireless network technology and wireless network technology. Among the 100 sample images, 50 included vehicles and 50 did not. Through experiments, it was found that the detection accuracy of cars and trucks without wireless network technology was 79% and 84%, respectively, while the detection accuracy of cars and trucks with wireless network technology was 92% and 89%, respectively. The wireless network-based vehicle detection technology improved the real-time performance of vehicle detection on the road with the help of cloud computing and edge computing technology, and enabled the vehicle detection technology to respond quickly according to system commands. The improvement of real-time performance and the implementation of rapid response have helped vehicle target detection technology achieve better performance in intelligent traffic.

Identity-Based Public Auditing for Cloud Storage of Internet-of-Vehicles Data

The Internet of Vehicles (IoV) , with the help of cloud computing, can provide rich and powerful application services for vehicles and drivers by sharing and analysing various IoV data. However, how to ensure the integrity of IoV data with multiple sources and diversity outsourced in the cloud is still an open challenge. To address this concern, this paper first presents an identity-based public auditing scheme for cloud storage of IoV data, which can fully achieve the essential function and security requirements, such as classified auditing, multi-source auditing and privacy protection. Particularly, we design a new authenticated data structure, called data mapping table, to track the distribution of each type of IoV data to ensure fine and rapid audits. Moreover, our scheme can reduce the overheads for both the key management and the generation of block tags. We formally prove the security of the presented scheme and evaluate its performance by comprehensive comparisons with the state-of-the-art schemes designed for traditional scenarios. The theoretical analyses and experimental results demonstrate that our scheme can securely and efficiently realize public auditing for IoV data, and outperforms the previous ones in both the computation and communication overheads in most cases.

Enterprise Management Optimization by Using Artificial Intelligence and Edge Computing

In the internet era, huge data is generated every day. With the help of cloud computing, enterprises can store and analyze these data more conveniently. With the emergence of the internet of things, more hardware devices have accessed the network and produced massive data. The data heavily relies on cloud computing for centralized data processing and analysis. However, the rapid growth of data volume has exceeded the network throughput capacity of cloud computing. By deploying computing nodes at the edge of the local network, edge computing allows devices to complete data collection and preprocessing in the local network. Thus, it can overcome the problems of low efficiency and large transmission delay of cloud computing for massive native data. This paper designs a human trajectory training system for enterprise management. The simulation demonstrates that the system can support human trajectory tracing and prediction for enterprise management.

An Efficient Certificate-Based Data Integrity Auditing Protocol for Cloud-Assisted WBANs

With the evolution of wireless body area networks (WBANs), wearable equipment will improve the human healthcare service. However, the medical data generated in WBANs increase dramatically with time, and the massive data cause the storage burden. With the help of cloud computing, the cloud service provider (CSP) can assist data owners in storing these data collected by sensors. By keeping their data in the CSP, the data integrity and authenticity is a big concern of data owners. To date, many data integrity auditing protocols have been proposed to address this issue. Most of them rely on traditional public-key mechanism, or identity-based cryptography (IBC), or certificateless cryptography (CLC). However, they suffer from the heavy cost of certificate management, key escrow, or the requirement of a secret channel for each user, respectively. To solve these drawbacks, we propose an efficient certificate-based data integrity auditing protocol for cloud-assisted WBANs. In our protocol, the computation cost in tag generation for a data block is fixed, and is independent of the size of the data block. We prove our protocol is secure in the random oracle model (ROM) and use the Java pairing-based cryptography library (JPBC) to implement the protocol. The experimental results show that our protocol is computationally efficient and practical.

Cloud Computing: A Review Paper

Abstract: Cloud computing is a major aspect for present time. In today’s world, it is going to became a part of life as it makes the work easy at every region as in business sector or for students or in any sector where we need to store data. With the help of cloud computing, life of people became easy because we don’t have to carry data in the form of register and log, we can simply check our data anywhere by my personal handset or personal laptop. It is more secure as well. It is less costly than other traditional computing. In this paper we will discuss about the services of cloud computing, then about the types of cloud computing, after that we will discuss its important factor that how is it beneficial for us? How can we use it in daily life? We will also discuss about the challenges happening in future due to spread of cloud computing

Awareness of cloud computing among the prospective teachers in the modern world

Cloud computing plays a vital role in education, politics, religion, transportation, relationships, medical check-ups, and so on. In education, online courses are carried out with the help of cloud computing. In cloud computing, expert conversations and classes delivered through any electronic device are protected on the server. The user can collect any information from the server through any search engine. There are so many platforms for downloading information for users. Electronic devices are very popular in this digital world. Some companies or individuals are introducing many applications for mobile phones and computers. One of the most useful options is search engines. It is very common to collect existing information on a server and it is a good communicator between users and cloud computing systems. Prospective teachers are the future teachers who will shape future citizens. The aim of the paper is to raise awareness of cloud computing among prospective teachers. This paper used a survey method to determine cloud computing awareness among prospective teachers and includes 61 samples from the College of Education. It uses the Cloud Computing Awareness Checklist tool to collect data for the present study. Hypotheses related to family type, locality, father's profession, father's education, and parents' income were found to have no significant differences. Thus, the result showed that prospective teachers have little knowledge of cloud computing. The researcher concluded that background variables are not significant. The essential things are the funds provided and the desire to learn. This will develop awareness and finally, the educator and prospective teachers raise awareness among prospective teachers and students, respectively. Educators encourage future teachers to collect more information about cloud computing on its own or with the help of an external facilitator.

Experimental Study of PaaS, Its Implementation Methods and Advantages and Challenges

This paper will explain the concept of PaaS in detail. PaaS is platform as a service. With the help of cloud computing, there are vendors who will provide platform like hardware and software online to be used by the employees of the business or organisation. The business can send their requirements to the vendor who will provide platform as a service to them based on per service charge basis. The paper will explain types of PaaS, Characteristics. Advantages and challenges in implementation of PaaS.

Accurate Range Query With Privacy Preservation for Outsourced Location-Based Service in IoT

With the maturity of Internet-of-Things technology, location-based service (LBS) is developing rapidly in intelligent terminal devices, and it brings new vitality to the fields of logistics, transportation, product traceability and so on. The popularity of LBS produces a lot of spatial data, which inevitably brings burden to the storage and management of LBS provider (LBSP). With the help of cloud computing and cloud storage, outsourcing spatial data to cloud server has become a new trend. However, due to the cloud server is not trusted, data outsourcing will face the problems of data disclosure and query disclosure. Range query is a common query in LBS, considering the situation of data outsourcing, this article proposes an accurate range query (ARQ) scheme, which can realize efficient range query while preserving LBSP's data privacy and user's query privacy from being disclosed to the cloud server. The ARQ scheme is suitable for spatial data in any form without being limited to the case that the data points are only integers, which has a certain practical significance. In addition, by dividing the region into atomic regions, ARQ can realize sublinear search time and ensure dynamic update of spatial data. We proved the security of the proposed scheme through security analysis, and demonstrated the effectiveness of the scheme through experiments.

Secure Efficient Revocable Large Universe Multi-Authority Attribute-Based Encryption for Cloud-Aided IoT

With the help of cloud computing, the ubiquitous and diversified Internet of things (IoT) has greatly improved human society. Revocable multi-authority attribute-based encryption (MA-ABE) is considered a promising technique to solve the security challenges on data access control in the dynamic IoT since it can achieve dynamic access control over the encrypted data. However, on the one hand, the existing revocable large universe MA-ABE suffers the collusion attack launched by revoked users and non-revoked users. On the other hand, the user collusion avoidance revocable MA-ABE schemes do not support large attributes (or users) universe, i.e. the flexible number of attributes (or users). In this article, the author proposes an efficient revocable large universe MA-ABE based on prime order bilinear groups. The proposed scheme supports user-attribute revocation, i.e., the revoked user only loses one or more attributes, and she/he can access the data so long as her/his remaining attributes satisfy the access policy. It is static security in the random oracle model under the q-DPBDHE2 assumption. Moreover, it is secure against the collusion attack launched by revoked users and non-revoked users. Meanwhile, it meets the requirements of forward and backward security. The limited-resource users can choose outsourcing decryption to save resources. The performance analysis results indicate that it is suitable for large-scale cross-domain collaboration in the dynamic cloud-aided IoT.

IEEE Access Special Section Editorial: Urban Computing and Intelligence

Urban computing utilizes unobtrusive and ubiquitous sensing technologies, advanced data management and analytics models, and novel visualization methods to create win-win-win solutions which intelligently improve people’s lives, urban environments, and city operation systems. With the help of cloud computing, the Internet of Things, device-to-device (D2D) communication, artificial intelligence (AI), big data, and urban computing and intelligence will bridge the gap of ubiquitous sensing, intelligent computing, cooperative communication, and mass data management technologies, to create novel solutions that improve urban environments, human life quality, and smart city systems. Thus, urban computing and intelligence has recently attracted significant attention from industry and academia for building smart cities.

Integration of Internet of Things, Cloud Computing: Review

As the Network of Things has grown exponentially, the Internet of Things devices generate tremendous data. IoT provides virtualization with or without the presence of being with the services. Managing this vast volume of data becomes a very tedious task. So in diverse sectors, including such as healthcare, education, agriculture, smart cities, there are various iot applications. Using different technologies, sensor data is acquired and data collection, data cleaning, data processing, and analysis are done with the help of cloud computing. We present a survey of the integration of the Internet of Things, cloud computing, and healthcare in this paper. The paper focuses on the different IoT Cloud computing platforms used with the Internet of Things and is an advantage of the healthcare domain’s usefulness.

Convergence of IOT in Tourism Industry: A Pragmatic Analysis

The term IoT commonly used abbreviation of ‘Internet of Things’ is trending and ascertaining the possible disruption in the tourism and hospitality industry. The industry is a complex interaction of several stakeholders and ancillaries working together for the experience of the tourist. It includes host government, local population, attractions, transportation, accommodation, food, and Beverages etc. tightly embodying the local trade, art, craft, festivals, religion, culture and many more. The tourist is the end consumer seeking experience and justifying with his Imagescape. The Imagescape could be different for the same destination in different people’s mind. The destination management companies work in order to continue, refine, or modify the current destination image to increase the tourist flow. With the IoT, Big Data, blockchain technologies, the destination will become a closely monitored space for the behavior of tourists, shopping patterns, visitation to each attraction, time spend and monetarily benefits generated. The reports will lead to well-calculated decision making for destination management and development of tourism and ultimately impacting the GDP growth. The Tourism industry has always been witnessing the changes and has been upgrading its attire accordingly. There was a time when internet overwhelmed the industry with multiple upgradations and now the Internet of things is going to influence the industry and tourist vividly.Tourism has been changing with the shifting technologies for several years and has shown multiple advancements to its operations and processes. Another technological trend of IoT is converting Tourism to the Smart Tourism and IoT is the core technology to transform the tourism industry with the help of cloud computing, mobile communication, blockchain, big data and artificial intelligence aligned to enhance the tourist experience. The hospitality industry is counted mainly on the utmost service standards and their executions with intangible characteristics. In such a complex industry, the innovative technology IoT has begun its influence to seek the customer’s satisfaction, cost saving, and business profit. Apart from the personalized rooms, predictive repair and maintenance the IoT will be enhancing the guest experience as well through the Electronic Key Cards which is sent by the hotel on your mobile phone to access the room directly without wasting their precious time in the reception of hotel. The hotel may also charge the guest as per the removal of beers cans from the mini bar of the room without the additional run through of a staff.The paper is crafted to identify the impacts of IoT on the tourism industry and proposes the model to streamline the industry with tourist’s movement in order to analyze the tourist’s experience completely. The Tourism industry is widespread and includes several stakeholders in overall channel of the tourist circuit. The industry is full of diversities and experiences in diversities. The trending technology may act as a thread to sew all in one comprising the experience and solve the issues of accurate data collection in the tourism industry. Fourth revolution technologies all together making an impact on the working of any domain, and hospitality and tourism industry is one of the front runners in implementing these technologies. The IoT has already started its impact all around the industry and tourism industry is thriving to match the pace to be smartly connected with its guests all the time in hotels transportation or attraction. The technology is still in the early stages of growth and implementation. The paper is divided into three sections of introduction, discussion on influence of Internet of Things technology in different fragments of tourism industry and the impacts of IoT concluded with a proposed model. The model presented in this paper analyzes the impacts of FIR technologies in particular of IOT in tourism domain.

IoMT-Based Automated Detection and Classification of Leukemia Using Deep Learning

For the last few years, computer-aided diagnosis (CAD) has been increasing rapidly. Numerous machine learning algorithms have been developed to identify different diseases, e.g., leukemia. Leukemia is a white blood cells- (WBC-) related illness affecting the bone marrow and/or blood. A quick, safe, and accurate early-stage diagnosis of leukemia plays a key role in curing and saving patients' lives. Based on developments, leukemia consists of two primary forms, i.e., acute and chronic leukemia. Each form can be subcategorized as myeloid and lymphoid. There are, therefore, four leukemia subtypes. Various approaches have been developed to identify leukemia with respect to its subtypes. However, in terms of effectiveness, learning process, and performance, these methods require improvements. This study provides an Internet of Medical Things- (IoMT-) based framework to enhance and provide a quick and safe identification of leukemia. In the proposed IoMT system, with the help of cloud computing, clinical gadgets are linked to network resources. The system allows real-time coordination for testing, diagnosis, and treatment of leukemia among patients and healthcare professionals, which may save both time and efforts of patients and clinicians. Moreover, the presented framework is also helpful for resolving the problems of patients with critical condition in pandemics such as COVID-19. The methods used for the identification of leukemia subtypes in the suggested framework are Dense Convolutional Neural Network (DenseNet-121) and Residual Convolutional Neural Network (ResNet-34). Two publicly available datasets for leukemia, i.e., ALL-IDB and ASH image bank, are used in this study. The results demonstrated that the suggested models supersede the other well-known machine learning algorithms used for healthy-versus-leukemia-subtypes identification.

Research on IT Management and Service of Small and Medium Sized Libraries Based on Cloud Computing and Virtualization Technology

At present, digital resources have become an important part of the collection resources of modern small and medium-sized libraries. As a new technology, cloud computing technology has been widely used in the field of small and medium-sized libraries, and has just begun to enter the vision of professional researchers. This paper studies the application of cloud computing and virtualization technology in IT management and service of small and medium-sized libraries. In order to better understand the application and help of cloud computing and virtualization technology in IT management and service of small and medium-sized libraries, this paper applies cloud computing and virtualization technology to it management and service in a university library, and then carries out a survey and statistics of the figure The library has developed a questionnaire to investigate the library staff and readers’ feelings about the application. The results show that under the support of cloud computing and virtualization technology, IT management and service for small and medium-sized libraries can significantly improve the management efficiency and service quality of libraries.

Intelligent Application of WSN for Forest Monitoring

A Large destructive fire that spread over a forest or area of woodland is a forest fire and another major problem is entering of wild animals into the cities, farm lands, highway roads that causes loss of humungous amount of Property, Wildlife, Ecosystem and Economy. The project is focused on creating a permanent solution for this problems. It consists of an integrated IoT based WSN (Wireless Sensor Network) system to detect, monitor and solve the issue without any manual involvement. With the help of cloud computing, regular monitoring is achieved. The system uses the latest Microcontroller, Wi-Fi communication and precision sensors to monitor the forest. The system also provides a quick response system for the fire and escaping of animals into the farmlands can be controlled at the earliest stage.

SGPM: a privacy protected approach of time-constrained graph pattern matching in cloud

Graph pattern matching (GPM) is an important operation on graph computation. Most existing work assumes that query graph or data graph is static, which is contrary to the fact that graphs in real life are intrinsically dynamic. Therefore, time-constrained graph pattern matching has been introduced. However, querying time-constrained graph pattern in a temporal graph is not an easy work because of the high computation complexity. Query outsourcing, with the help of cloud computing, is adopted in this paper. Outsourcing of data storage and query becomes increasingly popular due to the prevalence of cloud computing. However, sensitive data need to be encrypted before outsourcing for various privacy concerns. To execute queries over encrypted data is a very challenging problem and has received much attention recently. However, most existing approaches only support limited kinds of queries, moreover, they cannot be completely outsourced. In this paper, a Somewhat Homomorphic Encryption ($\mathcal {S}{\mathscr{H}}\mathcal {E}$) approach is adopted to design a protocol which enables general queries on encrypted data and query outsourcing as well. The key issue in the paper is to (1) enable the query provider to filter data rows with homomorphic encrypted result of comparison operators; (2) completely relieve the data owner of partaking of the process of queries. An effective dualcloud protocol (DCP) which enables the cloud to understand the result of comparisons though homomorphic encrypted values is proposed. Moreover, The efficiency of the baseline approach is greatly improved by packing and GPU-accelerating technologies. Experimental study shows that the optimized approach outperforms the baseline approach and the recently reported similar approaches.

Determining the Effectiveness of ‘Cloud Computing’ on Human Resource Management by Structural Equation Modeling (SEM) in Manufacturing Sector of West Bengal, India

The manufacturing industry is very much crucial for driving the economy of the nation. It has a direct impact on the GDP of any nation and also, it is very beneficial for a country to be strong in the manufacturing industry. This is also the case for a developing nation such as India. Hence, it is imperative for the organization to effectively manage their human resources to optimally utilize them as they are the non-perishable resources of the company. This could be done with the help of Cloud-Computing which is one of the advanced fields of elastic IT (Information Technology). This technology is continuously gaining momentum as it is relatively easier to use in E-HRM (Electronic-Human Resource Management) and also contains less initial investment. The objective of the study is to identify the factors that have an impact on the effectiveness of Human Resource Management by the help of Cloud computing. Various statistical tools like Exploratory Factor Analysis and Structural Equation Modeling have been executed in this study by SPSS 21 and AMOS 21 software.