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2024 International Conference on Computer engineering, Network and Intelligent Multimedia, CENIM 2024

作者： Acorda, Gladwin Lorenzo, Ariel M. Avila, Marianne Realin, Kathlene Solmayor, Jonathan Mabborang, Godwin Sam Calalo, Izella Mae School of Architecture Computing and Engineering University of Saint Louis Tuguegarao City Philippines University Research and Innovation University of Saint Louis Tuguegarao City Philippines

ISBN: (纸本)9798350368802

This study introduces an innovative waste disposal method by incorporating technology into a plastic bottle trash bin that offers Wi-Fi access as a reward for proper waste management. The 'smart bin' is designed to collect plastic bottles and grant internet time to users. It operates using a microcontroller with sensors that detect deposited bottles, displaying the number collected and the corresponding internet access time. Users can press a button to transfer this time to a TP-Link module, which provides a voucher code for internet access. Testing revealed that the bin's infrared (IR) sensor effectively counted bottles when inserted one at a time but struggled with multiple bottles, often registering just one. After five bottles, the system successfully generated a voucher code and reset the count. The study concluded that the smart bin accurately tracks bottles and provides corresponding internet access, ensuring a reliable user experience. © 2024 IEEE.

关键词： Wi-Fi

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Improved stability through self-localisation scheme in heterogeneous vehicular clustering

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International Journal of Vehicle Information and Communication Systems 2023年第3期8卷 252-265页

作者： Ahmad, Iftikhar Ahmed, Zaheed Al-Rashid, Muhammad Ahmad AJK Mirpur10250 Pakistan Faculty of Computing and Engineering University of Kotli AJK Pakistan Department of City and Regional Planning School of Architecture and Planning University of Management and Technology Lahore54770 Pakistan

Intelligent local data processing within vehicular ad hoc networks (VANET) may increase the capabilities of the internet of vehicles (IoVs). To share data effectively, vehicular clusters should be synchronised and stable. Vehicle needs uninterrupted global positioning system (GPS) signal for synchronisation purposes, especially in the urbane environment. GPS interruption leads to an unstable connection that is a big hurdle in developing cost-effective solutions for navigation and route planning applications. To solve this problem a self-location calculation scheme within the vehicular clustering process is proposed. The proposed self-location calculation algorithm enables vehicles to calculate their coordinates in the absence of GPS signals. A clustering mechanism is developed for sharing traffic information system (TIS) data among multiple vehicles over a particular road segment. Sharing of vehicular data in real-time helps vehicles to synchronise well. The developed scheme is simulated and compared with existing known approaches. The results show the better stability of our proposed mechanism over others. © 2023 Inderscience Enterprises Ltd.

关键词： Synchronization

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Predicting Intention to Recommend Digital Citizen Participation using Machine Learning 13

Predicting Intention to Recommend Digital Citizen Participat...

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13th IEEE International Conference on System engineering and Technology, ICSET 2023

作者： Hernandez, Alexander A. Abisado, Mideth B. Maceda, Lany L. Rodriguez, Ramon L. Montefalcon, Myron Darrel L. Padilla, Jay Rhald C. Sangalang, Hersel Danna E. National University College of Computing and Information Technologies Philippines Bicol University College of Science Albay Philippines National University - Dasmarińas School of Engineering Computing and Architecture Philippines

ISBN: (纸本)9798350340891

Digital citizen participation uses innovative technologies to enable, engage, and empower citizens to communicate with the government on different needs, concerns, and challenges. To this date, limited studies explain the intention and recommendation for digital citizen participation, particularly from the Philippines. Thus, this study aims to understand digital citizen participation through a survey that examines factors on the intention to use and recommend digital citizen participation among Filipino citizens. A conceptual model was developed based on trust, technology acceptance, and empowerment theory. The framework relationships were tested using machine learning algorithms. The results show that perceived ease of use, perceived usefulness, trust, and empowerment theory positively predicted the intention to recommend digital citizen participation. Furthermore, this study indicates that Filipinos have positive intention and are willing to recommend digital citizen participation. Finally, this work provides evidence of the explanatory power of the conceptual model through machine learning models on digital citizen participation. This work presents some important research and practical implications in digital citizen participation. © 2023 IEEE.

关键词： Developing countries

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Effects of Occupant Behaviour and Air Filtration on Indoor Air Quality in Social Housing 18

Effects of Occupant Behaviour and Air Filtration on Indoor A...

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18th International Conference on Indoor Air Quality and Climate, INDOOR AIR 2024

作者： Narayanan, Vishnupriya Valeriparambil Hashemi, Arman Elsharkawy, Heba Newport, Darryl Basaly, Lucienne G. School of Architecture Computing and Engineering University of East London United Kingdom Kingston School of Arts Kingston University United Kingdom Suffolk Sustainability Institute University of Suffolk United Kingdom

ISBN: (纸本)9798331306816

Indoor air pollution poses a significant threat to human health, making it crucial to identify sources, assess levels, and develop strategies to enhance indoor air quality. The main objective of this paper is to assess indoor air quality (IAQ) and the effectiveness of air purifiers and tailored behavioural interventions in improving IAQ in social housing properties in London. The methodology involved monitoring key pollutants, including carbon monoxide (CO), particulate matter (PM10 and PM2.5), total volatile organic compounds (TVOCs), and humidity levels using data loggers during three distinct phases: a) pre-intervention, b) with air purifiers, and c) after the behavioural intervention. The installation of air purifiers significantly reduced CO and PM10 levels, consistently maintaining them near or below recommended guidelines across all CSBs. However, the impact on TVOC levels was less pronounced, with levels often remaining above the recommended guideline, even after air purifier installation. Subsequent behavioural interventions aimed at educating occupants on best practices for reducing pollutant generation yielded variable results across CSBs and pollutants. The study demonstrated the potential benefits of combining air purifier installation with tailored behavioural interventions, effectively reducing CO, PM10, and PM2.5 levels. However, the persistent issue of elevated TVOC levels across all case study buildings underscores the need for further research and more comprehensive strategies, including source control measures. Future studies could explore the long-term sustainability of behavioural interventions, advanced air purification technologies targeting VOCs, and the development of integrated approaches for comprehensive indoor air quality management. © 2024 18th Conference of the International Society of Indoor Air Quality and Climate, INDOOR AIR 2024 - Conference Program and Proceedings. All rights reserved.

关键词： Indoor air pollution

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Risk Management for 5G-Enabled Internet of Things by Using Machine Learning: A Survey

Risk Management for 5G-Enabled Internet of Things by Using M...

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2024 Arab ICT Conference, AICTC 2024

作者： Alfaw, Aysha Elmedany, Wael Sharif, Mhd Saeed College of Information Technology University of Bahrain Sakhir Bahrain School of Architecture Computing and Engineering Department Computer Science and Digital Technologies UEL London United Kingdom

ISBN: (纸本)9798350342086

Nowadays, there is a noticeable increase in the development and use of the Internet of Things(loT). With this rapid increase, IoT devices may face several challenges when used in the real world through applications. Using 5G with large numbers of Internet-connected devices of IoT puts many devices at risk and requires risk management. The growing of IoT leads to the growth of cyber-attackers and allow them to expose the vulnerabilities. This paper will present the risk management of 5G-enabled IoT technology and the use of machine learning to mitigate the risk and reduce the attacks on these technologies, and finding solutions through previous researches. This research aims to identify and eliminate potential risks in the IoT based 5G by machine learning. The paper also aims to present a solution to the security problems and risks faced when integrating the fifth-generation network and the Internet of Things. With 5G-enabled IoT, the risk management helps organizations use emerging technologies effectively while mitigating potential underlying risks such as security breaches, and data loss. Authentication,encryption, access control, and communication security are essential for making security. Machine learning algorithms have the potential to remove many obstacles to implementing the security of the Internet of Things, paving the door for the use of sophisticated technology like 5G. With new 5G networks, it is expected that the current IoT will be significantly expanded, which will improve cellular operations and the security of IoT, as well as push the future of the Internet to its edges. Machine learning (ML) creates a secure and intelligent system and provides a robust security mechanism and dynamic for 5G networks. Therefore, this time will also present previous solutions with machine learning against the risks to IoT and 5G. This paper will present a set of previous studies related to insurance of risk management for the 5G-enabled IoT, Which aims to find previ

关键词： Adversarial machine learning

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Research on rapid measurement technology of railway line based on 3D coordinate acquisition trolley 6

Research on rapid measurement technology of railway line bas...

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6th International Conference on Geoscience and Remote Sensing Mapping, GRSM 2024

作者： Zhang, Maolin Cui, Mengzhen Li, Congxu Chen, Yuan Beijing University of Civil Engineering and Architecture School of Geomatics and Urban Spatial Informatics Beijing100044 China Institute of Computing Technologies China Academy of Railway Sciences Corporation Limited Beijing100015 China Beijing University of Civil Engineering and Architecture Beijing100044 China

ISBN: (纸本)9781510688018

The traditional method of remeasurement of operational railroad has many processes, complicated operations and low efficiency, and the time of railroad maintenance days is decreasing, so new demands are made on the remeasurement method of operational railroad. In response to this problem, this paper researches the rapid measurement technology of operational railroad to achieve the rapid and high-precision acquisition of spatial measurement data in a wide range of operational railroad and the rapid and high-precision measurement of railroad track line information. This paper mainly studies the railroad line 3D coordinate acquisition trolley and its acquisition system, mainly including the key technology research of data synchronization technology, data fusion Kalman filter technology, combined navigation solution technology and track flat and longitudinal section fitting optimization research. Through this research, the three-dimensional coordinate acquisition trolley of railroad line can obtain high-precision railroad track alignment information without relying on CPⅢ control network, reduce the number of times on the track, reduce the operation safety hazards, save cost and human resources. © 2025 SPIE.

关键词： Data fusion

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Analyzing the Pattern of the Jordanian Electricity Peak Load Amid Renewable Energy Transition Considering the GDP and Population Growth 14

Analyzing the Pattern of the Jordanian Electricity Peak Load...

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2023 14th International Renewable Energy Congress, IREC 2023

作者： Aljarrah, Rafat Afaneh, Tayma Ghazal, Mohammed Princess Sumaya University for Technology Electrical Engineering Department Amman Jordan School of Architecture Computing and Engineering University of East London London United Kingdom

ISBN: (纸本)9798350342840

This This paper aims to analyze the pattern of the electricity peak load of the Jordanian power network amid the renewable energy transition and to predict the peak load for the next ten years. It investigates the correlation between the population growth and the Gross Domestic Product (GDP), as an economic indicator, of the country and the peak load change through the years. Then, the yearly peak load is predicted using the linear regression model and an Autoregressive Integrated Moving Average (ARIMA) model to have a better insight on the power generation requirements for the next ten years. The results have shown that both the population growth and the GDP have a strong correlation with the yearly peak load of electricity. The results indicate that, if the same rate of growth of both the population and GDP is kept, the electricity peak load would increase from 3770 MW in 2021 up to around 5300 MW in 2034. This represents an increment of 41%, with a yearly rate of 3.4% approximately. In addition, the electricity peak load would be doubled by 25 years. © 2023 IEEE.

关键词： Electric loads

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NAVIGATING THE IMPACT OF HUGE ELECTRICAL DEMAND ON GRID THROUGH INTELLIGENTLY CONTROLLED RENEWABLES AND EMERGING V2G TECHNOLOGY 14

NAVIGATING THE IMPACT OF HUGE ELECTRICAL DEMAND ON GRID THRO...

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14th Mediterranean Conference on Power Generation Transmission, Distribution and Energy Conversion, MEDPOWER 2024

作者： Tariq, Raheel Ali, Zunaib Saleem, Komal Christofides, Nicholas School of Engineering London South bank University London United Kingdom School of Architecture Computing and Engineering University of East London London United Kingdom Electrical Engineering Computer Engineering and Informatics Frederick University Nicosia Cyprus Frederick Research Center Nicosia Cyprus

ISBN: (纸本)9781837242689

Among the biggest initiatives to help the UK reach its Net Zero goal are the conversion of the power grid to renewable energy sources (RESs) and the switch to all-electric vehicles (EVs) by 2050. However, because of the advent of dispersed unconventional energy sources and electric vehicles (EVs), the full switch to renewable energy sources and EVs poses a possible risk to power system stability, power quality, and energy management. To intelligently regulate the flow of energy and enhance the current power system, it is crucial to employ appropriate energy management strategies. This paper aims to establish a microgrid that is grid-connected and utilises multiple energy sources, including solar, battery energy storage, and electric vehicles. The goal is to create an intelligent algorithm that efficiently controls these resources and mainly enable bi-directional EV operation for vehicle-to-grid (V2G) application, resulting in both financial and environmental advantages. The main objective is to maximise the microgrid's overall profitability while minimising carbon emissions and effectively managing energy demand and network stability. It has been shown that utilising EVs as storage units via beneficial V2G technology not only stabilises renewable energy generation but also provides economic advantages. © The Institution of engineering & Technology 2024.

关键词： Microgrids

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Rail Transit Event Extraction based on the Fusion of Semantic and Local Dependency Features 15

Rail Transit Event Extraction based on the Fusion of Semanti...

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15th IEEE International Conference on Knowledge Graph, ICKG 2024

作者： Chen, Qiang Meng, Haining Bao, Yihao Yang, Mingsong Tong, Xinyu Zhao, Qin Khan, Muhammad Bilal Hei, Xinhong Xi'an University of Technology School of Computer Science and Engineering Xi'an China Xi'an University of Technology School of Computer Science and Engineering Shaanxi Key Laboratory of Network Computing and Security Technology Xi'an China Xi'an University of Technology School of Civil Engineering and Architecture Xi'an China

ISBN: (纸本)9798331508821

Event extraction in rail transit plays a vital role in all stages of design, construction, and final acceptance. Event extraction is a key part of building event logic graph (ELG). However, the difficulty in obtaining semantic features and event local dependencies poses a challenge to accurate event extraction, which hinders the informatization and intelligent development of rail transit projects. To address these challenges, we proposes an event extraction method that fuses semantic and local dependency features. The study initially preprocesses the rail transit design codes dataset and performs sequence labeling. Then, the event trigger words are mined by combining the term frequency-inverse document frequency (TF-IDF) and minimum edit distance (MED) algorithms. Based on the semantic similarity measurement method and the trigger word mining results, the features representation of event semantic information is enhanced by using the Bidirectional Encoder Representations from Transformers (BERT) model and Bi-directional Long Short-Term Memory (BiLSTM) model. At the same time, event arguments are mined and a local dependency graph is generated based on their mining results, and then the enhanced local dependency features are obtained by using the graph convolutional network (GCN). Finally, the event semantic features and local dependency features are fused, and the conditional random field (CRF) is used to predict the labels to obtain the event extraction results. Through the comparison with five baseline methods on the datasets of rail transit design codes, it is found that the Precision, Recall, and F1 score of the proposed method are improved, with an average improvement of 9.604% on Precision, 9.342% on Recall, and 9.730% on F1 score, respectively. The contribution of the sub-modules to the overall performance is further evaluated through ablation experiments, which confirms the effectiveness and feasibility of the proposed method. © 2024 IEEE.

关键词： Semantics

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Enhancing Photovoltaic Panel Efficiency through a Dual-Sided Water Spray Cooling System

Enhancing Photovoltaic Panel Efficiency through a Dual-Sided...

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2024 International Conference on Computer engineering, Network and Intelligent Multimedia, CENIM 2024

作者： Silva, Marvin S. Lorenzo, Ariel M. Soliven, Gamaliel I. Gumaru, Alfredo M. Soriano, Leslie C. Taguiam, Christian M. University of Saint Louis School of Architecture Computing and Engineering Department Cagayan Tuguegarao City Philippines University of Saint Louis University Research and Innovation Tuguegarao City Philippines

ISBN: (纸本)9798350368802

Solar panels experience efficiency losses due to high temperatures, which can decrease power output by 0.3%-0.5% per degree above 25°C, with extreme heat causing up to 25% efficiency loss, as prolonged exposure and heat absorption negatively affect the performance of photovoltaic cells. The study investigates the effectiveness of a water spray cooling method to enhance the electrical efficiency ofphotovoltaic (PV) panels under peak solar irradiation conditions. By cooling both sides of the PV panel simultaneously, the researchers aimed to mitigate the adverse effects of high temperatures on panel performance. Experimental results demonstrated that the water-cooling method reduced the panel temperature to approximately 40. 73°C, leading to a remarkable total increase of 68.67% in electric power output and a total increase of 67.86% in electrical efficiency, equating to an effective improvement of 27.63 %. These findings indicate that the proposed cooling technique significantly enhances the operational efficiency of PV systems, making it a viable solution for improving energy output in high-temperature environments. Implementing such cooling strategies can not only optimize the performance of solar panels but also contribute to the long-term sustainability of solar energy systems, particularly in regions experiencing high solar radiation. © 2024 IEEE.

关键词： Photovoltaics

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