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Components, Technologies, and Market of Road Traffic Management System in Global Scenarios: A Complete Study

Components, Technologies, and Market of Road Traffic Managem...

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2021 IEEE international conference on Innovative computing, Intelligent Communication and Smart electrical Systems, ICSES 2021

作者： Agarwal, Piyush Sharma, Sachin Matta, Priya Graphic Era Deemed to Be University Department of Computer Science and Engineering Dehradun India

ISBN: (纸本)9781665435215

Traffic management system (TMS) plays a very important role in everyone's life. Directly or indirectly maximum of our tasks get affected by or related to the traffic. For a better service and travel experience, it is important to know the different signs and symbols of the road. Therefore, this paper also includes a discussion on the different components of TMS, traffic zones set during the maintenance of the traffic infrastructure. This paper includes 5E's of traffic management for road safety. Different technologies that can be used in TMS to make the system more efficient and effective are also discussed. The various research work related to TMS accomplished in the last few years has also been discussed. This work also includes the traffic control system based on technologies like IoT, Artificial Intelligence, etc. Some Intelligent Traffic Management Systems (ITMS) that are being used in different countries are also included © 2021 IEEE.

关键词： Roads and streets

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Ensuring the Data Security and Integrity over Cloud computing Environment using Novel Cipher Strategy

Ensuring the Data Security and Integrity over Cloud Computin...

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IEEE international conference on engineering Education: Innovative Practices and Future Trends (AICERA)

作者： Praveen Kumar E B. Yasotha Narmadha PG P. Chandrakala C. Ushapriya G Chamundeeswari Department of CSE (IoT) Sri Krishna College of Technology Coimbatore Tamil Nadu India Department of Data science and Business systems SRMIST kattankulathur Tamil Nadu India Department of Computer Science and Engineering Panimalar Engineering College Chennai Tamil Nadu India Department of Electrical and Electronics Engineering Prince Shri Venkateshwara Padmavathy Engineering College Chennai Tamil Nadu India Department of Artificial Intelligence and Machine Learning St. Martin's Engineering College Telangana India Department of Electronics and Communication Engineering Saveetha Engineering college Chennai Tamil Nadu India

The advent of cloud computing has revolutionized the Internet. Users may effortlessly collaborate, back up, and access their information from any location thanks to cloud computing. When it comes to providing IT enabled services via the internet, cloud computing is the clear winner. Cloud computing allows a large number of people to share resources like computers, programs, and servers. Users of cloud services often have no idea where their data actually resides or where it came from. Users of cloud computing services are understandably concerned about the safety of their data once it has been uploaded to the cloud with respect to service providers. Privilege control, comprehensive encryption algorithms, management of keys, provenance instances and global consistency verification are only some of the numerous data privacy and security issues that occur as a result. This study introduces a novel cloud security strategy, Cloud based Novel Cipher Strategy (CNCS), and analyzes issues related to the safety and integrity of data stored in the cloud. We're looking into many data safety related factors here. In this article, we'll look closely at a selection of data protection strategies now in use throughout the globe to guarantee the highest level of security possible. Later, the study delves into the various methods of cloud based data security. To prevent unwanted access, alteration, or deletion of dynamic as well as static information, a procedure for validating their integrity is outlined. The proposed system CNCS efficiency is evaluated in the resulting section through the following metrics such as: integrity level, data storage efficiency and security level. All these metrics are evaluated based on the size of data, in which it is tested with respect to number of days the proposed scheme is tested over the industrial environment to prove the performance and efficiency of the proposed approach.

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control for Quality of the Separated Products of a Butylene-Butane Distillation Column Based on High Order Iterative Learning control

Control for Quality of the Separated Products of a Butylene-...

引用

Complex Systems and Intelligent science (CSIS-IAC), international Annual conference on

作者： Xiumei Zhang Kailong Zhou Hui Li Changlei Xia Ze Zhang Fangda Liu College of Electrical and Electronic Engineering Changchun University of Technology Changchun Jilin China Jiangsu Co-Innovation Center of Efficient Processing and Utilization of Forest Resources International Innovation Center for Forest Chemicals and Materials Materials Science and Engineering Nanjing Forestry University Nanjing Jiangsu China

This paper presents the design of an advanced control system for product quality of a butylene-butane distillation column (BBDC) based on High Order Iteration Learning control (HOILC). The multicomponent distillation process was adapted to a pseudo-binary distillation process for the development of automatic control systems for the product's quality. Starting from this assumption, dynamic models of the process were obtained for the input-output channels reflux flowrate – concentration of the pseudo-light component and bottom product flowrate – concentration of the pseudo-heavy component. To enhance the control accuracy of product quality, this paper adopts a high-order iterative learning algorithm to optimize the accuracy of the product quality control system for the butene-butane distillation tower. Compared with conventional iterative learning, a high-order iterative learning algorithm contains more degree of freedom, which significantly improves the algorithm performance, speeds up the convergence process, reduces the required number of batches, and ultimately achieves the goal of reducing the number of trays and improving efficiency. Simulation and modeling of a product quality control system for a butene-butane distillation column in Simulink, and its validation through MATLAB coding and Simulink, have demonstrated that High-order ILC effectively improves the performance and cost of the product quality control system for this type of distillation column.

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Prediction the Number of Lamps Required for the Lighting System According to the JKR Lux Standards by Using the Artificial Neural Network Method

Prediction the Number of Lamps Required for the Lighting Sys...

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IEEE international conference on control System, computing and engineering (ICCSCE)

作者： Nuzul Lokmanhakim Zulkifli Mohamad Adha Mohamad Idin Samshul Munir Muhamad Ahmad Asri Abd Samat Khairul Azman Ahmad Noorezal Atfyinna Mohd Napiah Centre for Electrical Engineering Studies Universiti Teknologi MARA Cawangan Pulau Pinang Permatang Pauh Malaysia Faculty Applied Science Universiti Teknologi MARA Cawangan Pulau Pinang Permatang Pauh Malaysia

This paper aims to develop an advanced neural network-based model for accurately predicting the number of lamps required in lighting system designs, with a focus on cost-effectiveness and compliance with JKR Standards. The scope of the research encompasses the design and evaluation of the model using a comprehensive dataset and a range of parameters. The methodology involves leveraging machine learning techniques, specifically neural networks, to analyze various factors and optimize the lamp prediction process. Extensive testing and validation are conducted to assess the model’s performance and efficiency. The findings demonstrate the superiority of the proposed model in terms of accuracy, efficiency, and cost-effectiveness compared to traditional methods. The study contributes to the field of lighting design by providing a reliable and automated solution that reduces human error and improves energy efficiency, occupant satisfaction, and safety. The findings of this research indicate that the ‘trainlm’ algorithm is the most effective for predicting the number of lamps needed. It achieved a regression value of 1.00 and a low error percentage of only 0.499%. These results demonstrate the algorithm’s accuracy and suitability for the task at hand. The conclusion highlights the significance of the developed model in streamlining the design process and offers recommendations for future work, such as exploring additional factors and evaluating the model on diverse datasets. Overall, this research enhances the understanding and application of neural networks in lamp prediction for optimal lighting system designs.

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ML-Based Wildfire Prediction and Detection

ML-Based Wildfire Prediction and Detection

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computing and Machine Intelligence (ICMI), international conference on

作者： Chiragee C. Joshi Jaya S. S. K. Payyavula Soham Patel Yasser M. Alginahi Electrical and Computer Engineering Dept. University of Windsor Windsor Canada Computer Science Dept. Adrian College Michigan USA

ISBN: (数字)9798350372977

ISBN: (纸本)9798350372984

This paper provides a comprehensive study on prediction and detection of wildfire using Machine Learning and Deep Learning algorithms. Due to the current environmental trends, wildfire possess a great threat to the ecosystem and human lives at a great cost. Multiple factors are the root cause for wildfires which include environmental factors like temperature, humidity, air pressure index, forest terranean, vegetation. Taking these factors into consideration, a Machine Learning model was built considering diverse algorithms to learn the previous trends and predict future wildfires instances. Based on the satellite imagery of previous wildfires, using CNN and AlexNet algorithms to detect wildfires that are currently taking place for early detection so to contain and control the fire without it causing any damage. Amalgamating these two algorithms, in a single graphical user interface, enhances user accessibility and convenience, providing an invaluable tool in wildfire management. The algorithm achieved an accuracy of average 96.33 % to predict wildfires and was able to detect them based on images at the rate of 93.66%.

关键词： Temperature sensors Wildfires Machine learning algorithms Accuracy Prediction algorithms Market research Data models

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Hyperspectral Technology for Oil Spills Detection by Using Artificial Neural Network Classifier 18th

Hyperspectral Technology for Oil Spills Detection by Using A...

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Proceedings of the 18th international conference on Soft computing Models in Industrial and Environmental Applications, SOCO 2023

作者： Carrasco-García, María Gema Rodríguez-García, María Inmaculada González-Enrique, Javier Cubillas-Fernández, Paloma Rocío Ruiz-Aguilar, Juan Jesús Turias-Domínguez, Ignacio José Department of Industrial and Civil Engineering School of Engineering University of Cádiz Ramón Puyol Av. Algeciras11202 Spain Department of Computer Science Engineering School of Engineering University of Cádiz Ramón Puyol Av. Algeciras11202 Spain Department of Thermal Machines and Motors School of Engineering University of Cádiz Ramón Puyol Av. Algeciras11202 Spain

ISBN: (纸本)9783031425288

Hyperspectral sensors in marine pollution detection, such as oil spills from maritime traffic, represent an innovative and smart solution that addresses rapid detection and supports early oil spill cleanup operations. A spectroradiometer has been used to collect the spectral signatures of polluted water, including different thicknesses of oil films to achieve concentration determination. The spectral resolution provided by the spectroradiometer (1 nm), which works from the visible-near infrared (VNIR, 350–1000 nm) to the short-wavelength infrared (1000 - 2500 nm), provides a continuous spectral signature yielding rich and complete spectral information about the material. The high volume of data generated by hyperspectral technology requires a feature selection procedure for better management and optimization of computing resources. In this study, Principal Component Analysis (PCA) has been the statistical method used for dimensional reduction. The results are very promising, since PCA succeeded in defining the original dataset in a three-dimensional space, maintaining 80% of its variance. Likewise, it has also been possible to establish that the wavelengths ranged between 449 nm and 549 nm, and the infrared from 750 nm ahead, are the most influential wavelengths in the characterization of the data. Classification task has been performed with ANNs, whose hyperparameters have been determined with Bayesian Optimisation. A shallow ANN with 10 neurons has been selected with an accuracy of 100% in the detection of polluted water and 96,7% accuracy in the determination of the classes provided, with a failure rate of 16.7% for the discrimination of oil concentration alone. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Oil spills

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Cloud-Based Framework for Robot Operation in Hospital Environments 14th

Cloud-Based Framework for Robot Operation in Hospital Enviro...

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14th APCA international conference on automatic control and Soft computing (controlO)

作者： Ferreira, Nuno M. Fonseca Boaventura-Cunha, Jose Coimbra Polytechn ISEC Coimbra Portugal Univ Tras Os Montes & Alto Douro Vila Real Portugal INESC TEC Campus FEUP Porto Portugal

ISBN: (纸本)9783030586553;9783030586539;9783030586522

The robotics field iswidely used in the industrial domain, but nowadays several other domains could also take advantage of it. This interdisciplinary branch of engineering requires the use of human interfaces, efficient communication systems, high storage and processing capabilities, among other issues, to perform complex tasks. This paper aims to propose a cloud-based framework platform for robot operation in a hospital environment, addressing some challenges, such as communications security and processing/storage features. The recent developments in the artificial intelligence field and cloud resources sharing are allowing the penetration of robots in unstructured environments. However, some new challenges and solutions need to be tested in real environments. Our main contribution is to decrease the time-consumption related to processing and storage costs, associated with the physical processing resources of the robots. Also, the proposed methods provide an increase of the processing variables that are not yet present in the physical resources, such as in the case of robots with limited processing time or storage capabilities. This paper presents a platform based on Cloud computing with services to support processing, storage and analytics applied to hospital environments. The proposed platform enables to achieve a decrease in the time-consumption, especially when it is intended to retrieve information about all robot activities.

关键词： Robotics Autonomous robots control Cloud Security

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An Intelligent Internet of Things (IoT) Powered Railway Track Crack Detection Scheme Based on Smart Sensors Association

An Intelligent Internet of Things (IoT) Powered Railway Trac...

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Innovative computing, Intelligent Communication and Smart electrical Systems (ICSES), international conference on

作者： P. Prince P. Seethalakshmi Prasad D R. Kanchana L. Bharathi S. Leones Sherwin Vimalraj Department of CSE Vel Tech High Tech Dr. Rangarajan Dr. Sakunthala Engineering College Chennai Department of AIMLDS QIS College of Engineering and Technology Prakasam District AndhraPradesh India Department of EEE Sona College of Technology Salem Department of CSE Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Chennai Department of IT QIS College of Engineering and Technology Ongole AndhraPradesh Department of Electronics and Communication Engineering Panimalar Engineering College Chennai

ISBN: (数字)9798331543624

ISBN: (纸本)9798331543631

This paper presents an IoT -powered railway track crack detection system that uses a combination of smart sensors and autonomous vehicles to detect cracks and obstacles in railway infrastructure. The system incorporates ultrasonic sensors, infrared (IR) sensors, and LED-LDR assemblies, enabling real-time monitoring and reporting of railway track conditions. Wireless communication protocols such as Wi- Fi, RF transmitters, and GPS are utilized to transmit data to central control systems. Through testing, the combined sensor setup demonstrated the highest crack detection accuracy of 98%, outperforming individual sensors with accuracies of 94 % for ultrasonic sensors, 90% for IR sensors, and 80% for LED-LDR. The system's response time averaged 460ms in the combined setup, with the LED-LDR setup being the slowest at 580ms. The system also showed resilience across varied environmental conditions, proving its robustness in both high and low temperature, humidity, and lighting scenarios. This efficient, solar-powered system reduces manual inspection efforts and ensures continuous, reliable operation. The proposed system offers an innovative, cost-effective solution to enhance railway safety and prevent potential accidents caused by track defects.

关键词： Accuracy Rail transportation Sensor systems Acoustics Real-time systems Sensors Internet of Things Intelligent sensors Autonomous vehicles Global Positioning System

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control System Prototype of Feeding And Water Draining in Bucket Catfish Cultivation Based on Arduino Uno

Control System Prototype of Feeding And Water Draining in Bu...

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international conference on Sustainable engineering and Creative computing (ICSECC)

作者： Mohammad Taufik Bintang Putra Mahardika Arjon Turnip Department of Electrical Engineering Universitas Padjadjaran Sumedang Indonesia

Catfish is one of the most popular fish in Indonesia. Fish Cultivation in Bucket (Budikdamber) is a potential solution that is encouraged by the community to increase production in the fishery sector. This study aims to build a prototype of an automatic feeding system and control of water turbidity in catfish farming. This research uses ultrasonic input sensor HC-SR04, RTC DS3231, and turbidity sensor SEN0189 as inputs processed in the Arduino UNO microcontroller which produces output on the servo motor, buzzer, and solenoid valve. The level of routine feeding, the status of the void of feed, the level of turbidity (NTU), and the level of the water level in the bucket became the measuring parameters in this study. The results of this experiment showed automatic feeding 3 times a day, namely at 07.30 WIB, 11.30 WIB, and 18.30 WIB. The buzzer will sound when the feed container is empty. Draining the water is carried out when the turbidity of the water reaches 718.84 NTU and is filled again when the turbidity of the water reaches 544.76 NTU. The maximum water level limit is 21.36 cm and the minimum is 33.67 cm as seen from the sensor distance.

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Role Access control Search Scheme Based on Attribute Encryption 5th

Role Access Control Search Scheme Based on Attribute Encrypt...

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5th international conference on Innovative computing, IC 2022

作者： Cao, Xinhui Ye, Jun School of Cyberspace Security Key Laboratory of Internet Information Retrieval of Hainan Province Hainan University Haikou China

ISBN: (纸本)9789811941313

In order to facilitate data sharing, the data owner stores the data on the cloud server, but for data security, the data is generally encrypted based on cryptography when outsourced to the cloud. Use attribute-based encryption (ABE) to encrypt data Encrypt and upload to the ECs to prevent data abuse and theft. When retrieving data through searchable encryption, there will be data leakage, that is, data that cannot be decrypted by the user will also appear. In this paper, a more fine-grained role access control search scheme based on attribute encryption is proposed, using role-based access control (RBAC) Associate users with system roles. Data owners can specify flexible access policies for the encryption stored in the ECS. When data users retrieve data, the ECS filters the data that does not meet user permissions through the internal authentication system to prevent data leakage. Compared with existing systems in the market, this scheme can effectively prevent privacy data According to the disclosure, it has a higher fine-grained division, which makes the ECS unable to obtain the user’s sensitive information when providing services. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Cryptography

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