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A Review of current practices and challenges in Green Data Centers: renewable energy sources, waste heat recovery, and intelligent management systems

A Review of current practices and challenges in Green Data C...

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Euromicro conference on Parallel, distributed and Network-Based Processing

作者： Marta Boscariol Elisa Cacciaguerra Paola Gasbarri Daniele Accardo Silvia Meschini Lavinia Chiara Tagliabue Department of Management University of Turin Turin Italy Department of Computer Science University of Turin Turin Italy

ISBN: (数字)9798331524937

ISBN: (纸本)9798331524944

As digital transformation advances, Data Centers are crucial in supporting global digital infrastructure but contribute substantially to energy consumption and carbon emissions. Green Data Center technologies emerged to address such sustainability challenges, integrating energy-efficient designs, renewable energy, and waste heat recovery solutions. The review explores advancements in sustainable Data Centers, focusing on Building Information Modelling (BIM), Digital Twins (DTs), and intelligent management systems, that help mitigating environmental impacts. BIM and DTs support realtime monitoring, predictive analysis, and optimized energy management, helping operators minimize cooling needs, reduce inefficiencies, and maximize renewable energy *** interest in renewable energy sources such as solar power is increasing, highlighting hydrogen fuel cells potential in providing a scalable, low-emission alternative to conventional backup power. Waste heat recovery also plays a crucial role in Green Data Centers, with initiatives repurposing heat for district heating, industrial processes, and building heating. Current applications include Data Centers where heat recovery systems supply residential heating, support algae farms, and enhance university campus *** energy efficiency, Green Data Centers contribute to smart grid stability. Load-shifting capabilities enable power usage to be adjusted during peak and off-peak times, enhancing grid resilience and promoting sustainability. Future trends include AI-driven resource management, further carbon footprint reduction via green energy procurement, and advanced load distribution *** review synthesizes current research and practices, showcasing sustainable technologies in Green Data Centers, presenting case studies of successful implementations. It also highlights promising applications and existing challenges in achieving carbon-neutral infrastructures.

关键词： Data centers Reviews Green buildings Focusing Energy efficiency Digital twins Waste heat Sustainable development Heat recovery monitoring

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Innovative Technologies monitoring the State of Geographically distributed Networks Industrial Facilities (Using the Example of Pipeline Transport)

Innovative Technologies Monitoring the State of Geographical...

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2021 IEEE international conference "Quality Management, Transport and Information Security, Information Technologies", T and QM and IS 2021

作者： Kukharenko, Elena G. Alyushina, Svetlana G. Yankevskiy, Alexey V. Moscow Technical University of Communication and Informatics Faculty of Digital Economy and Mass Communications Moscow Russia Technical University of Communication and Informatics College of Telecommunications Moscow Moscow Russia Peoples Friendship University of Russia College of Telecommunications Moscow Technical University of Communication and Informatics Engineering Academy Moscow Russia

ISBN: (纸本)9781665433020

A necessary element of the system of automated management of geographically distributed production facilities is multicriteria control of their safety. The urgency of the problem of ensuring industrial safety increases when it comes to dangerous and especially dangerous production facilities, the elimination of the consequences of accidents at which are associated with high environmental and economic damage to the state economy. The article substantiates the criteria for the analysis of scientific developments in the field under consideration. The results of the analysis of developments in the field of monitoring the state of geographically distributed production facilities by means of intelligent software and hardware complexes and systems using fiber-optic sensors, etc. are presented. Based on the justified criteria, the selection of technical solutions for the creation of a geographically distributed system for monitoring the state of production facilities of the oil and gas industry was made. © 2021 IEEE.

关键词： Accident prevention

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A Fast Identification Method for Morchella Growth Stage Based on Vision Transformer

A Fast Identification Method for Morchella Growth Stage Base...

引用

control, Electronics and computer Technology (ICCECT), IEEE international conference on

作者： Jia Ning Zheng Chunjun Intelligent Management Center Dalian Neusoft University of Information Dalian China School of Software Dalian Neusoft University of Information Dalian China

ISBN: (数字)9798350380958

ISBN: (纸本)9798350380965

We introduce a rapid identification method for morchella. Based on the unique biological characteristics and growth environmental requirements of morchella, the efficient and accurate identification of key growth stages of morchella is achieved through the integration of information acquisition technology. In order to further improve recognition accuracy, the Multi Stage Vision Enhanced Position Encoding Vision Transformer (MS-EP ViT) model is adopted. By introducing multi-stage input embedding, enhanced position encoding, and optimized Transformer Encoder layers, the performance of the model in identifying different growth stages of Morchella mushrooms is significantly improved. The experimental results show that the model has achieved significant improvements in recognition accuracy and stability, and the rationality of hyperparameter settings has been verified through convergence and parameter sensitivity experiments. Overall, we provide a more accurate and efficient identification method for monitoring the growth of Morchella, which helps to better understand the growth of Morchella and provides scientific basis for optimizing its growth environment.

关键词： Sensitivity Computational modeling Optimization methods Production Transformers Encoding Data models

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A Review on environmental Sustainability Using Machine Learning Applications

A Review on Environmental Sustainability Using Machine Learn...

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IoT Based control Networks and intelligent Systems (ICICNIS), international conference on

作者： E. Nirmala Manish Yadav Palanichamy Naveen M. Maragatharajan M. Suresh Pranjal Bhargava School of Computing Science and Engineering VIT Bhopal University Kothri Kalan Madhya Pradesh India School of Computing Science engineering and Artificial Intelligence VIT Bhopal University Kothri Kalan Madhya Pradesh India Department of Electrical and Electronics Engineering KPR Institute of Engineering and Technology Coimbatore Tamil Nadu India

ISBN: (数字)9798331518097

ISBN: (纸本)9798331518103

environmental sustainability reduces the destruction of natural resources in the hands of mother earth for next generation. Due to the development of cities and its social and economic factors leads the major role of any such destruction. It affects huge volume of biological system in terms of environmental pollution, change in climate and respective population growth. Henceforth, the general population is severely affected with their quality of life in the present scenario. This research study discusses about various resources that are affected severely due to the environmental factors have stated with the proven evident. Along with this various prediction technology using machine learning procedures are discussed in detail to prevent any such destruction by improving the present style of work. The prediction of any such destruction exploiting resources like land, water, mineral and planetaries creates its impact in the form of climatic changes, as a result of this we are facing drought, earthquakes and landslide. Apart from preventing techniques over plantation of greeneries, it is necessary to implement techniques towards efficient use of resources monitoring is essential features. All these things are now essentially managed with the help of computer aided technology. Further the effective usage of environmental factors results into safe future for the next generation. This can be achieved by using AI with SUV to increase the prediction accuracy. Further this article is directed towards future direction to prevent and use the natural resources is discussed for the benefit of population around the world.

关键词： Natural resources Pollution Reviews Green products Urban areas Plantations Machine learning Terrain factors Next generation networking Water resources

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Crop Growth monitoring System Based on Infrared Thermal Imaging and Internet of Things Technology

Crop Growth Monitoring System Based on Infrared Thermal Imag...

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Electrical, Automation and computer Engineering (ICEACE), international conference on

作者： Yangde Lin Zhiyuan Hu Xiaoran He Jiahong Wu Rui Xu Hongxiu Wang Tianjin University of Science and Technology Tianjin China

In order to solve the shortcomings of the existing intelligent agricultural system and promote the rapid development of agricultural modernization, the project is based on the existing intelligent agricultural system. With the help of sensors, controllers, smart cameras, smart cameras and other Internet of Things equipment, the project collects various growth indicators of crops themselves and their growth environment, and comprehensively monitors the meteorological, soil and other environmental change trends, crop growth, and the operation status of agricultural facilities at the agricultural production site. The software system developed by the supporting project team analyzes the collected information and compares it with the preset data to obtain the current growth status of crops. The real-time transmission and real-time sharing of agricultural production information are realized. In addition, the system can also analyze the data in a certain period of time, predict and control the future growth status and possible pests and diseases, and realize the scientific and refined planting of crops. After the implementation of the project, it will effectively solve a series of problems such as the shortage of human resources in the process of large-scale planting and the low yield caused by the untimely monitoring of crop growth. While reducing human input, it has realized the increase of crop income, greatly reduced the planting cost of farmers, improved the economic, social and ecological benefits of facility agriculture, and has good development prospects.

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Design of Smart Garden Watering and Lighting Using Arduino

Design of Smart Garden Watering and Lighting Using Arduino

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international conference on Developments in eSystems Engineering (DESE)

作者： Hadeel Amjed Saeed Nuha A. Hamad Sumaya Hamad Information Systems Departmen University of Anbar Anbar Iraq Computer Science Department University of Anbar Anbar Iraq Computer Network Department University of Anbar Anbar Iraq

A developing technology called a “smart garden” employs analytics, sensors, and automation to make gardening simpler and more productive. Plant cultivation is a laborious process, so to produce crops healthily, farmers must routinely visit the farming area to assess the many environmental parameters, including humidity, temperature, soil moisture, and light intensity. Through the interlinking of these microclimatic factors, all parameters can be monitored automatically without human assistance using automatic garden monitoring and control. In this study, we employ an Arduino microcontroller to activate a light and a motor for pumping water, respectively, and monitor and control humidity, soil moisture, and temperature using sensors. With the use of the Android app, information will be supplied to the monitoring screen in the event of any abnormal circumstances, and the appropriate solution will be offered. The control and monitoring system for smart gardens is moving toward an intelligent, remotely accessible, real-time, and fully automatic system. A simple way to provide the perfect humidity, temperature, and moisture conditions for plant growth has evolved. As a result, this research tried to understand the idea, trends, and perception of smart gardens, a relatively new idea.

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Raspberry Pi based intelligent greenhouse Internet of Things platform 23

Raspberry Pi based intelligent greenhouse Internet of Things...

引用

Proceedings of the 2023 5th international conference on Internet of Things, Automation and Artificial Intelligence

作者： Shanhu Chen Danchun Li Junneng Liu Runkai Wei Guangzhou Xinhua University China

ISBN: (纸本)9798400716485

With the development of smart agriculture, realizing accurate monitoring and management of greenhouse agriculture environment becomes the key to improve the efficiency and quality of agricultural production. This study aims to develop a Raspberry Pi based intelligent greenhouse IoT platform to enhance the automation and intelligence of greenhouse agriculture. This platform utilizes Raspberry Pi as the core controller, integrates multiple environmental sensors for real-time data acquisition, such as temperature and humidity, light intensity, etc., and optimizes the accuracy of the data through Kalman filtering algorithm. The Raspberry Pi also assumes the function of an IoT gateway to securely and efficiently transmit data to the cloud for remote storage and processing. In addition, this study also developed the supporting mobile APP and computer client software to provide users with an intuitive interface for data monitoring and remote control. In terms of energy management, by applying the BBPSO algorithm to optimize the angle of solar panels, this platform effectively improves the energy utilization efficiency and guarantees the sustainable operation of the system. The results of this study not only improve the management efficiency and crop production quality of greenhouse agriculture, but also provide a useful reference for the future technological development of smart agriculture.

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intelligent Tracking Technology of Sensitive Data Based on Tag Distribution Learning 3

Intelligent Tracking Technology of Sensitive Data Based on T...

引用

2022 3rd international conference on computer Information and Big Data Applications, CIBDA 2022

作者： Zhou, Xiaoming Yu, Hai Yu, Pengfei Ziyi, Teng State Grid Liaoning Electric Power Supply Co. Ltd State Grid of China Shenyang China State Grid Liaoning Information and Communication Company State Grid of China Shenyang China State Grid Key Laboratory of Information & Network Security Global Energy Interconnection Research Institute Co. Ltd Nanjing China

ISBN: (纸本)9783800758760

The frequent interaction and sharing of massive data in the big data environment brings increasingly serious data security problems, such as the theft of data by illegal users, the unauthorized use of data by legitimate users, and the illegal dis-closure and dissemination of data. In practical application, the phenomenon of data leakage is inevitable due to the influ-ence of environmental and human factors, but there are few studies on the traceability of data after data leakage. Data traceability means that when the data leaked to a third party is captured, the source head and relevant responsible person can be traced by analyzing the relevant characteristics of the illegal data. This paper studies the intelligent tracking tech-nology of sensitive data based on tag distribution learning, which consists of three stages: tag generation technology of sensitive data content, tag distribution generation method and tag distribution comparison technology of sensitive data. Firstly, aiming at the problem that the existing machine learning algorithm has low recognition accuracy for sensitive data with no significant features, the sensitive data content tag generation technology is studied, and the tags of structured data and unstructured data are extracted. Secondly, the generation method of label distribution is studied to realize data multi-label identification based on label distribution descriptor model. Finally, the label distribution comparison technol-ogy of sensitive data is studied to realize accurate identification and tracking of sensitive data based on label distribution learning. Aiming at the problem of frequent data flow and difficult monitoring of sensitive data flow, the generation of sensitive digital tags and the construction of association relationship in the process of data flow are studied, and the data tracking technology based on tag recognition is studied to realize the dynamic tracking and security monitoring of sensi-tive data. © VDE VERLAG GMBH -

关键词： Sensitive data

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intelligent monitoring System of Materials Subject Laboratory Based on IoT 4

Intelligent Monitoring System of Materials Subject Laborator...

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4th international conference on computer Network, Electronic and Automation, ICCNEA 2021

作者： Yang, Fan Zhao, Tongxuan Zhang, Huixiang Queen Mary University Of London Engineering School Northwestern Polytechnical University Xi'an China School Of Automation Northwestern Polytechnical University Xi'an China School Of Cybersecurity Northwestern Polytechnical University Xian China

ISBN: (纸本)9781665444866

In view of the situation that may cause flammable gas, harmful gas, smoke leakage and other damage to the health of scientific research personnel and the temperature and pressure in the experimental instrument exceed the upper limit of danger during the operation of the university materials subject laboratory, research and development Based on LAN, 4G, 5G materials subject laboratory intelligent IoT monitoring system, it is divided into four layers from bottom to top: perception execution layer, control service layer, transmission network layer, terminal application layer. After real-time measurement of abnormal environmental parameters, the IoT system automatically warns and regulates the drive exhaust fan to ensure the health of the experimental scientific research personnel. In addition, it monitors the temperature and pressure during the experiment. Once the limit is exceeded, it automatically drives the actuator to prevent fires, explosions and other accidents. © 2021 IEEE.

关键词： Internet of things

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Proceedings of: 2020 international conference on computer, control, Electrical, and Electronics Engineering, ICCCEEE 2020

Proceedings of: 2020 International Conference on Computer, C...

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2020 international conference on computer, control, Electrical, and Electronics Engineering, ICCCEEE 2020

ISBN: (纸本)9781728191119

The proceedings contain 125 papers. The topics discussed include: design of a fully automated adaptive quantization technique for vehicular communication system security;semi-centralized blockchain based distributed system for secure and private sharing of electronic health records;application-based selection for 5g networks;an intelligent plug and play system for sensor installation;hyper-heuristic approaches for the travelling thief problem;sentiment analysis for Sudanese Arabic dialect using comparative supervised learning approach;an interactive dashboard for monitoring the spread of COVID-19 in Sudan;and reduction of basher city’s distribution losses using medium voltage network.

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