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Edge and Fog computing for IoT: A Case Study for Citizen Well-Being 7th

Edge and Fog Computing for IoT: A Case Study for Citizen Wel...

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7th EAI international conference on science and technologies for Smart Cities, SmartCity360° 2021

作者： Bianconi, Luca Lechiara, Yuri Bixio, Luca Palermo, Roberto Pensieri, Sara Viti, Federica Bozzano, Roberto Gruppo Sigla S.R.L via Finocchiaro Aprile 31/5a Genoa16129 Italy FlairBit S.R.L via Maragliano 6/5 Genoa16121 Italy via de Marini 16 Genoa16149 Italy via de Marini 16 Genoa16149 Italy

ISBN: (纸本)9783031063701

Citizen well-being during indoor and outdoor activities is a prerogative in the paradigm of smart city. Air quality, together with thermo-hygrometric, light and noise comfort are some of the most relevant parameters that affect the perception of the state of well-being. An internet of things (IoT) network based on LoRaWAN end-nodes has been set up with the aim to provide an approach to improve the well-being of citizens living in an urban district in Savona (Liguria region, Italy) under the umbrella of the PickUP project. The main focus of the project was the design of innovative methods and tools for energy and environmental management and the reduction of consumption in heterogeneous districts. The proposed IoT architecture comprises a Fog node constituted of a Raspberry Pi 4 to analyze in near-real-time the heterogeneous data and to provide feedback to the proper actuators in case of need of changes in the ventilation and heating of the occupied room. Moreover, the infrastructure provides insights about the air quality in outdoor areas to local authorities, in order to implement mitigation action or strategies. Results demonstrate the usefulness of the proposed architecture with a precise focus on social impact, but also reveal economic implications linked to an intelligent use of energy resources and to the development of energy efficiency strategies. © 2022, ICST Institute for Computer sciences, Social Informatics and Telecommunications Engineering.

关键词： Energy efficiency

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An Empirical Design of IoT based Health Surveillance Scheme for Coronavirus Affected Patients

An Empirical Design of IoT based Health Surveillance Scheme ...

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international conference on science Technology Engineering and Management (ICONSTEM)

作者： M. Swarna R. Geetha G. Saranya Shakthi Murugan K H C. Gnanaprakasam Department of Electronics and Communication Engineering Dr. M.G.R. Educational And Research Institute University Chennai Tamilnadu India Department of Computing Technologies SRM Institute of Science and Technology Chennai India Department of Electronics and Communication Engineering Sri Krishna College of Engineering and Technology Coimbatore Department of Electronics and Communication Engineering Narayana Engineering College Gudur AndhraPradesh Department of Artificial Intelligence and Data Science Panimalar Engineering College Chennai Tamilnadu India

In the year of 2019, a major destruction was raised to all over the Country called as Coronavirus, which is also termed as Covid-19. This is one of the serious threat and many people lost their lives due to the affection of Coronavirus disease. Due to the spread ratio and nature, nobody is interested to properly monitor the patients who are all affected with this disease. So, that a new technology is required to monitor the health conditions of patients and instantly reporting the details to the respective person and guardian as well. As technology advances, doctors are constantly on the lookout for new automated gadgets that might make it simpler to detect abnormalities in the human body. The Internet of Things makes it possible to create cutting-edge, transparent healthcare support structures. This paper introduced a new health monitoring scheme called Covid Patients Health Analyzer (CPHA), in which this methodology is associated with the help of trending technology called Internet of Things (IoT). This system introduces an Internet of Things assisted patient health surveillance technology, which aids medical professionals in remotely measuring the blood concentration, pulse rate, respiration level and temperature of the respective patient. Both the person's pulse rate and blood oxygen sufficiency levels are read using an intelligent sensor called MAX3100, whereas the individual's temperature is scanned with a powerful sensor called DS18B20. Using a humidity identification sensor, one may determine the relative humidity of a given space. All required information will be encoded and decoded by the ESP32 module before being processed. The patients Fingers are hooked up to sensors as well as readings are shown on a respective computer or smartphone. After putting the suggested system through its paces, the working is clearly tested and it delivers the desired results in good manner. By monitoring the process remotely, medical personnel no longer need to worry about c

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Verification of Job Authenticity using Prediction of Online Employment Scam Model (POESM)

Verification of Job Authenticity using Prediction of Online ...

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international conference on Computational science and Technology (ICCST)

作者： Banu Priya Prathaban Subash Rajendran G Lakshmi D. Menaka Department of ECE Sri Sairam Engineering College Chennai India Depatment of Computing Technologies SRM Institute of science and Technology Chennai India Department of CSE Sathyabama Institute of science and Technology Chennai India

ISBN: (纸本)9781665476560

In the recent times it is found to that there is a growing interest in Internet of Things (IoT) and its respective sophisticated cloud architectures. However, such development does not ensure the confidentiality, integrity due to its security vulnerabilities in its improvements. Therefore data breaching occurs rapidly in all sectors. Nowadays, several job-seekers are becoming the prime victim for such digital loophole fraudsters, when there is an advertisement for bulk requirement. In order to reduce frauds and scams that are designed to take advantage of people who seek jobs, a model to predict the genuineness of posting digital vacancies for job is real or fake. This paper presents the implementation of Prediction of Employment Scam Model (POESM), intending for the classification of fraudulent and non-fraudulent digital job posting advertisements. In our work, we used eight techniques such as Logistic Regression, Naive Bayes, Multiple Layer Perceptron, K-Nearest Neighbor, Decision Tree, Random Forests, Adaboost, Gradient Boosting classifiers. To analyze the dataset, supervised machine learning techniques is used to capture several essential information. Empirical results are found based on Accuracy, F1-Score, Cohen-Kappa Score, and MSE declares that Random Forest classifier is best suited for the prediction of online fraudulent requirements. The proposed POESM strategy can be a promising solution for identifying the genuineness of vacancies for job posted via internet.

关键词： Cloud computing Scientific computing Computational modeling Employment Predictive models Fraud Internet of Things

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Text-Based Delay Prediction in a Public Transport Monitoring System 21

Text-Based Delay Prediction in a Public Transport Monitoring...

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29th ACM SIGSPATIAL international conference on advances in Geographic Information Systems, SIGSPATIAL 2021

作者： Jastrzȩbska, Agnieszka Homenda, Wladyslaw Warsaw University of Technology Faculty of Mathematics and Information Science Warsaw Poland Artificial Intelligence University of Information Technology and Management Rzeszow Poland

ISBN: (纸本)9781450386647

computing technologies have already established their place in various areas of public transport control in smart cities. While the analysis of signals coming from various sensors is executed at a very high level of sophistication, information expressed by humans in natural language is still not being used in a way that takes advantage of its full potential. Existing research on text mining in public transport monitoring is focused mainly on event detection. In this paper, we present a novel approach to vehicle delay prediction based on text data. The proposed method fuses information coming from standard sources (sensors) with text messages, to construct a regression model, that predicts delays for previously unseen messages describing road conditions. The method has been implemented based on an existing public transport monitoring system in Warsaw, Poland. In the paper, we discuss it briefly. Delay prediction based on information expressed in natural language will not replace standard methods for delay prediction that involve the use of vehicle sensors. However, it offers an attractive alternative to mine for knowledge from sources such as social media. © 2021 ACM.

关键词： Forecasting

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Answering an Amharic Language Semantic Question over Interlinked data

Answering an Amharic Language Semantic Question over Interli...

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international IEEE conference on Signal-Image technologies and Internet-Based System

作者： Gashaw Demlew Fekade Getahun Faculity of Computing Jimma University Jimma Ethiopia Department of Computer Science Addis Ababa University Addis Ababa Ethiopia

The web has generated a large amount of structured data, and the number of Amharic-language online data portals is growing. As a result, intuitive ways of integrating and accessing this data are becoming increasingly important. Various question-answering approaches for different languages have been proposed to extract answers from interlinked datasets. In this paper, we propose a novel question-answering approach for Amharic, allowing users to ask questions using their terminology and receive direct answers. To accomplish this, the approach addressed the three major challenges that are required to meet users’ information needs from the interlinked datasets. These are understanding users’ questions, resolving lexical ambiguity, and fusing data from multiple sources. Apart from this, the approach can be used to answer different question types such as factual, aggregation, comparison, and superlative. A prepared Amharic test dataset was used to evaluate the approach. It achieved an average f-score of 0.83.

关键词： Technological innovation Terminology Social networking (online) Semantics Linguistics Resource description framework Portals

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InterCriteria Analysis of Public Health data in Bulgaria

InterCriteria Analysis of Public Health Data in Bulgaria

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international conference on Intelligent and Fuzzy Systems, INFUS 2020

作者： Sotirova, Evdokia Vasilev, Valentin Sotirov, Sotir Bozov, Hristo Prof. Dr. Assen Zlatarov University Prof. Yakimov Blvd. Burgas8010 Bulgaria Oncology Complex Center-Burgas 86 Demokratsiya Blvd. Burgas8000 Bulgaria

ISBN: (纸本)9783030511555

The assessment of the system of public health has been receiving significant importance over the past years, because it reflects the trend in optimizing the effectiveness of the health services. The article uses a recently defined intelligent decision-making method based on an extension of fuzzy logic called InterCriteria Analysis (ICA). Object of the study of (the) ICA are real data in the field of public health connected with in-patient, out-patient health care establishments and their regional distribution in Bulgaria for the years 2010–2018. Using the ICA approach, we can identify the relationships between and among indicators of health care facilities and nursing staff, statistical regions and districts, the doctors in the healthcare facility by medical specialties, and more. The metrics that have the greatest dependencies and the contrary indicators that are often independent of one another. This way we can monitor their demeanor over time. © 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Public health

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Detection Of Ships in The Ocean Using Deep Learning Algorithm

Detection Of Ships in The Ocean Using Deep Learning Algorith...

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international conference on Innovative Sustainable Computational technologies (CISCT)

作者： Amit Kumar Mishra Neeraj Kumar Pandey Vivek Kumar Umang Garg Mayank Singh Computer Science and Engineering Graphic Era Hill University Dehradun Uttarakhand India School of Computing DIT University Dehradun Uttarakhand India Computer Science and Engineering Teerthanker Mahaveer University Moradabad Uttar Pradesh India

ISBN: (纸本)9781665474177

Maritime transportation is one of the most common and growing transportation schemes in the ocean. Autonomous ships have grown in popularity since the introduction of self-driving autos, particularly the submarines as well as weapon equipped ships that uses by military persons. Ship recognition and categorization in remote sensing photos is important for the security of marine-areas, also some more activities like peoples who use to catch fishes illegally and to control or to view the pollution in the sea. The detection and categorization of ships in remote sensing pictures is vital for maritime safety as well as other applications like traffic surveillance, illicit fishing and their prevention (sea). With the increasing number of satellite image data, automatic ship identification and remote sensor picture classification is an essential application for both the military and civic sectors, but there are many problems like clouds, weather which cause distraction. So, in this paper we have suggested a deep learning model which is based on CNN that is convolutional neural net. By using CNN, we can increase throughput, efficiency & also remote sensing picture which is used for image processing is fast and reliable.

关键词： Deep learning Oceans Weapons Transportation Traffic control Throughput Convolutional neural networks

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A review on Artificial Intelligence based Sign Language Recognition Techniques

A review on Artificial Intelligence based Sign Language Reco...

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international conference on Contemporary computing and Informatics (IC3I)

作者： Kakoli Banerjee K G Harsha Pradeep Kumar Indira Vats P Vinooth Piyush Dasila Naved Akhtar Ajay Kumar Prajjwal Gautam Department of Computer Science J.S.S. Academy of Technical Education Noida

The World Wide Web Consortium describes web accessibility as the ability to access any information online regardless of the technology used and interacting with the interface of the web if required. Over the last few decades, significant efforts have been made in the field of web accessibility. Successful tools were developed leveraging technologies such as Artificial Intelligence, Speech Recognition systems and motion detection using Computer Vision. Sign Language is a form of non-verbal, hand movement or gesture based mode communicating thoughts and ideas. It is the primary way of communication for many people, majorly including differently abled people, such as people with speech-impairments. Despite being popular amongst people who are unable to speak or hear, there exists a great disparity in the knowledge of Sign Language in the general population consisting of able-bodied individuals. This necessitates the existence of a system that bridges this gap, and allows for efficient interpretation of Sign Language. Sign Language recognition is a growing field of interest in the domain of Artificial Intelligence, and many tools have been created to automate this process using image recognition techniques. These techniques are used to classify sign language and map them into their corresponding meaning in the English language. The steps required in this include the acquisition of data, extraction of relevant features followed by the training of the classifier. This paper gives an overview of the level of work done in this field, and delineates the scope of some models created for this purpose. It also discusses the challenges that are being faced and the scope of work that is yet to be done.

关键词： Training Technological innovation Image recognition Training data Gesture recognition Speech recognition Assistive technologies

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Performance investigation of fiber to the home (FTTH) ingress network based on gpon with optisystem 1st

Performance investigation of fiber to the home (FTTH) ingres...

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1st international conference on Frontiers in Smart Systems technologies, ICFSST 2019

作者： Kavitha, T. Prabhakar Reddy, K. Sravani, J. Veltech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Chennai India

ISBN: (纸本)9789811550287

Nowadays in our day to day life very high-speed data rate is very exigent. It can be increased according to the users of Internet with the applications like smart phone, video surveillance, live broadcasting of news, video conference, etc. Fiber to the home (FTTH), also called "fiber to the premises" (FTTP), is the installation of optical fiber from a central point directly to individual buildings such as residences, apartment buildings and businesses to provide unprecedented high-speed Internet access. FTTH dramatically increases the connection speeds available to computer users compared with other technologies. This paper investigates the performance of the FTTH, and the performance is analyzed by using the optisystem software. The proposed architecture minimizes the Bit error rate (BER) and increases the Q-factor. The minimum BER attained for upstream configuration with a distance of 15 km is 1.01489e−073 and for downstream configuration is 1.24672e−026. Maximum Q-factor for upstream configuration at a length 15 km is 18.1225 and for downstream configuration is 10.6166. The Q-factor for both the cases meets the standards because both the configuration values are above 6. The standard sensitivity of this configuration is −28 dBm, and the calculation values using optisystem is −26.205 dBm. So, the proposed system is feasible. © Springer Nature Singapore Pte Ltd 2021.

关键词： Bit error rate

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Prevention of Misuse of Information Technology in the Health Industry

Prevention of Misuse of Information Technology in the Health...

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international conference on computing, Engineering, and Design (ICCED)

作者： Hastanto Januar Ahmad Teddy Mantoro Ivan Yulivan Medical Intelligence Postgraduate Program State Intelligence College Bogor Indonesia Department of Computer Science Media-Tech Lab Sampoerna University and State Intelligence College Jakarta Indonesia

ISBN: (纸本)9781665453905

Technological advances in the field of digitalization and networks of information have made the world enter the industrial revolution 4.0 including in the health and medical sector. This revolution is marked by the easy exchange of information in a short amount of time without being limited by geographical constraints and the shift from paper-based documents to digital. The health sector has also begun to adopt the 4.0 revolution by making health services more accessible to the public such as online medical applications, the use of electronic medical records, and the use of big data to personalize medical therapy for sick people. Even though the use of this information technology has a lot of benefits, there is also potential to be misused such as the purchase of dangerous medicines and leakage of patient's medical data also inadequate support from telemedical services due to a lack of guidance for personnel which has the potential to harm both physically and materially. Indonesia currently does not have a defense mechanism and regulations to protect its citizen from the misuse of information technology in the health industry. Systematic efforts are needed so that the use of information technology can run properly and safely. There need to be some measures to prevent the unlawful use of health information technology such as strict regulation and monitoring, defense against cyber hacking and leakage, also adequate training for the operators of health services in using the technology

关键词： Industries Training Systematics Regulators Regulation Security Information technology

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