2021 IEEE International Conference on Mobile Networks and Wireless Communications (ICMNWC)最新文献

{"title":"Design and Development of Smart Driver Safety System using the Behavioural and Physiological Data Approach","authors":"Deepak Varadam, Kadarabenchi Valmiki Ganesh","doi":"10.1109/ICMNWC52512.2021.9688514","DOIUrl":"https://doi.org/10.1109/ICMNWC52512.2021.9688514","url":null,"abstract":"An automotive smart driver safety system for collision avoidance and warning is implemented by adopting invehicle communication. The implementation of the system is carried out for monitoring the driver of the vehicle using the behavioural and physiological data approach. The behavioural and physiological data is monitored by using various parameters of the driver like fatigue, drowsiness, attention diversion, abnormal heart rate, and stress levels. ARM CORTEX A-53 & ATMEGA 326 microcontrollers are used as a central processing unit. Sensors and a camera are used to monitor the driver as input. GPS receiver is used for collecting the vehicle information and direction of movement of the vehicle. This information along with the monitoring data is transmitted to the ARM CORTEX A-53 processor. Appropriate microcontroller coding is chosen. If any abnormal activity is detected the warning message will be displayed on an LCD screen or an alarm sound is given to the driver. The project proposes a low-cost and improved approach for Collision Warning and Accident Avoidance systems. A stable and reliable smart driver safety system is developed by considering ARM CORTEX A-53 microcontroller and GPS, GSM as a data communication platform.","PeriodicalId":186283,"journal":{"name":"2021 IEEE International Conference on Mobile Networks and Wireless Communications (ICMNWC)","volume":"91 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117098516","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Emergency Ambulance Service Framework Using PSO and RFID","authors":"Shanoorbaba Mabub Yargatti, Udaykumar Naik","doi":"10.1109/ICMNWC52512.2021.9688508","DOIUrl":"https://doi.org/10.1109/ICMNWC52512.2021.9688508","url":null,"abstract":"The critical patient movement to the hospital requires a reduction in ambulance travel time to provide quality health care to the patient. To achieve this goal, our work uses two advanced technologies: Particle Swarm Optimization (PSO) and Radio Frequency IDentification (RFID). Particle swarm optimization algorithm helps in route optimization to locate the nearest ambulance for emergency patient calls. The RFID innovation is utilized to execute shrewd traffic light control. RFID introduced at traffic light tracks RFID labeled rescue vehicles and sends the information to the cloud. Thus, the implementation of this work is to have optimized method for the ambulance selection and ease of ambulance movement at the road intersection. This developed prototype system model with RFID and PSO technologies works as supporting traffic management aid in critical patient movement.","PeriodicalId":186283,"journal":{"name":"2021 IEEE International Conference on Mobile Networks and Wireless Communications (ICMNWC)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125272176","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Web Based Approach for Navigation Technology using Fused Location API","authors":"Bharath Ravi Prakash, S. S. Kulkarni","doi":"10.1109/ICMNWC52512.2021.9688537","DOIUrl":"https://doi.org/10.1109/ICMNWC52512.2021.9688537","url":null,"abstract":"The method employed in today's scenario is service-oriented web applications to turn business model methods into processes where they can be integrated. The key idea was to develop a web application that would allow friends, relatives to be monitored. The proposed application is capable of gathering information from GPS and storing the main web application that helps for specifics of the maps (Google Map API). This paper presents a new web based approach which primarily aims at improving the storage and data security since they are of prime importance when any navigation based technology is concerned.","PeriodicalId":186283,"journal":{"name":"2021 IEEE International Conference on Mobile Networks and Wireless Communications (ICMNWC)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124476742","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Defending Multiple Attack Via Multiple Algorithms With Fault Tolerance","authors":"M. Grace, M. Sughasiny","doi":"10.1109/ICMNWC52512.2021.9688377","DOIUrl":"https://doi.org/10.1109/ICMNWC52512.2021.9688377","url":null,"abstract":"Smart devices are prone to numerous attacks these days. Many number of malwares attacks with many ways. Increasing attacks with many attacking ways evades standard prediction methods. The most dangerous attacks among them is colluding attacks. This collusion method make prediction more complex. Data privacy and system integrity will be fragile. Information leakage will be high through this collusion attacks. The android malware detection methods use static, dynamic and hybrid method. From Code control flow graphs patterns will be extracted through this method. both the direct and indirect communication channels will be tracked by these methods.","PeriodicalId":186283,"journal":{"name":"2021 IEEE International Conference on Mobile Networks and Wireless Communications (ICMNWC)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129763102","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Enhanced Cloud Optimization Model for CSP, Tenant and User Through Container","authors":"Muthakshi. S, M. K","doi":"10.1109/ICMNWC52512.2021.9688531","DOIUrl":"https://doi.org/10.1109/ICMNWC52512.2021.9688531","url":null,"abstract":"The system leverages an optimization scheme for the tenant, client and CSP. This guided optimization model design acts as a intermediate SP (service provider) that guides the user for effective data streaming and resource allocation. A proper resource allocation strategy by checking the availability, size, security, and cost-effective service providers are deliberated. A deep neural learning is emphasized to produce a complete analysis on cloud. An optimization technique used to systemize the information in cloud. A new systematic Enhanced profit/loss (EPF) calculator implemented to calculate the profit or loss that are established during resource allocation. In case the loss rate is more then it gets controlled during the transaction itself. By analyzing the ratings, comments and the report a feedback record produced that helps in choosing a trustworthy container to the tenant. The tenant suggestthe particular trustworthy container to the user likewise the cyclic recommendation process is proceeded. From the proposed optimization model the experimental results are deliberated. The results demonstrates a profit for several users and CSP bu eduring a organized allocation scheme.","PeriodicalId":186283,"journal":{"name":"2021 IEEE International Conference on Mobile Networks and Wireless Communications (ICMNWC)","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129901758","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An Automated Deep Learning Model for Detecting Sarcastic Comments","authors":"Jaico Jose, Preethi N","doi":"10.1109/ICMNWC52512.2021.9688410","DOIUrl":"https://doi.org/10.1109/ICMNWC52512.2021.9688410","url":null,"abstract":"The concept of Natural Language Processing is immensely vast with a wide range of fields in which ideas can be explored and innovations can be developed. An algorithm based on deep learning is used to detect sarcasm in text in this paper. It is usually only possible to detect sarcasm through speech and very rarely through text. 1.3 million comments from Reddit were analyzed, of which half were sarcastic and half were not, and then various deep learning models were applied, such as standard neural networks, CNNs, and LSTM RNNs. The best performing model was LSTM-RNNs, followed by CNNs, and standard neural networks came last. With textual data, it is much harder to understand whether the other person is being sarcastic or not, it can only be understood by listening to their tone of voice or looking at their behaviour. The purpose of this paper is to demonstrate how to detect sarcasm in textual data using deep learning models.","PeriodicalId":186283,"journal":{"name":"2021 IEEE International Conference on Mobile Networks and Wireless Communications (ICMNWC)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123190759","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Internet of Medical Things Applications for Healthcare Industry","authors":"H. Vidhya, Abinaya Inbamani, S. Lingeswaran, R. Abishek, R. Harish, K. Kishor","doi":"10.1109/ICMNWC52512.2021.9688401","DOIUrl":"https://doi.org/10.1109/ICMNWC52512.2021.9688401","url":null,"abstract":"Health of the human beings is really need to be taken care at the most. At present, the medical field is progressing well and facilitating the people to consult doctor even online which we normally term as telemedicine. Such a system should be automated to make it even more effective. Healthcare automation ensures physical and moral support to the patient and reduces the need of a caretaker near the patient. In order to make automation possible in health care, Internet of Things (IoT) contributes a lot. The proposed work is based on Internet of Things being connected to electronic devices via a public or private cloud to catch or screen information and empowers them to naturally trigger certain occasions or events. It also includes various monitoring system in healthcare such as heart beat rate monitor, pill bottle and drips bottle remainder, electronic paralysis patient caretaker. These monitoring systems are used to monitor patient health remotely using sensors and mobile communication devices. The heart beat sensor is used which monitors the heart rate of a person and transmits the heart rate readings over Internet and during abnormality, an alert message will be sent to the doctor’s mobile. As it very evident that the paralyzed people will not be able to communicate properly to explain what they need, the proposed system helps the disabled person to show hand gestures which in turn will display the need of the patient on an LCD screen. It is very common that due to human nature, quite good number of people skips their medication. In order to ensure proper medication, the proposed system also involves a technique to remind the people to take pill on time. The collection of pills is made possible by using a mechanical set up which consists of motor and a wheel. One more issue has been addressed by proposed system to indicate the level of glucose in drips bottle and provides information to the care taker or medical assistant to replace the drips bottle before it is completed.","PeriodicalId":186283,"journal":{"name":"2021 IEEE International Conference on Mobile Networks and Wireless Communications (ICMNWC)","volume":"63 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126313045","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Brain Tumor Detection Using Convolutional Neural Network","authors":"G. Kumar, Puneet Kumar, D. Kumar","doi":"10.1109/ICMNWC52512.2021.9688460","DOIUrl":"https://doi.org/10.1109/ICMNWC52512.2021.9688460","url":null,"abstract":"A brain tumor (BTR) is the development of aberrant and uncontrolled cells in the brain. The detection of a BTR in its early stages is essential in the treatment of its sufferers. There are various ways to diagnose a BTR but Imaging is one of the accurate ways to find the critical one. There are various imaging tests available like Magnetic Resonance Imaging (MRI), Computerised Tomography (CT) scan, and Positron Emission Tomography (PET). MRI is preferable among all because it is highly adept at capturing images that help doctors determine if there are abnormal tissues within the body. Detecting BTR by just looking into MRI images is prone to human errors and the patient may reach the end stage of the disease. Therefore, the main objective of this research is to create a Convolutional Neural Network (CNN) that can detect and classify whether a patient has a BTR or not. In the proposed method, ‘Leaky ReLU’ activation function with convolution 2D layer (Conv2D + Leaky ReLU) combine and compares the model accuracy with a pre-implemented CNN model i.e., (Conv2D + ReLU) layers combinations. The proposed model achieved 78.57% validation accuracy, which is higher than the normal pre-implemented CNN model. However, the training accuracy score of both the model is 99.20%.","PeriodicalId":186283,"journal":{"name":"2021 IEEE International Conference on Mobile Networks and Wireless Communications (ICMNWC)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127799425","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"RPL over Internet of Things: Challenges, Solutions, and Recommendations","authors":"Khalid A. Darabkh, Muna Al-Akhras","doi":"10.1109/ICMNWC52512.2021.9688375","DOIUrl":"https://doi.org/10.1109/ICMNWC52512.2021.9688375","url":null,"abstract":"Internet of Things (IoT) has recently attracted significant research interest. Routing protocols have a vital task in meeting the needs of IoT devices with the necessary ability to interwork seamlessly. The major target of this work is to help the IoT research community in understanding all aspects of the most popular IoT routing protocol, which refers to the IPv6 routing protocol for Low-Power and Lossy Networks (RPL). In this work, after investigating the major challenges of RPL and studying a body of the proposed RPL solutions, which are fragmented based on these challenges, we get ultimately capable of shedding the light on all challenges encountered by IoT researchers along with their role in enhancing the RPL and providing what is expected to be dealt with them in a professional manner bearing in mind the limitations of IoT nodes. Not only that, but the research history of RPL is professionally analyzed based on RPL challenges over the years 2010 and 2020 using Google Scholar, Scopus, and IEEE Xplore. Interestingly, the conclusions and recommendations of this study are presented along with effective directions of the future of RPL, to be followed, and its applicability. As a result, the authors anticipate that this study will be useful to all RPL researchers and designers.","PeriodicalId":186283,"journal":{"name":"2021 IEEE International Conference on Mobile Networks and Wireless Communications (ICMNWC)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133035030","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Sign Language to Voice Translator Using Tensorflow and TTS Algorithm","authors":"G. K, Akkash. C, Sagaya Selvaraj. A, Arockiya Rayal Ruffus. M, Cesario De Cruz. E","doi":"10.1109/ICMNWC52512.2021.9688545","DOIUrl":"https://doi.org/10.1109/ICMNWC52512.2021.9688545","url":null,"abstract":"In this system, it helps to convert the sign language to voice with hand gestures understanding and capture the motion of hands. Many sign languages are natural languages, but they are differing in construction from oral languages used in proximity to them, and are employed mainly by deaf people in order to communicate. It is based on a Raspberry Pi with a camera module and is programmed in Python with the Open-Source Computer Vision (Open CV) library as a backend. A built-in image processing algorithm on the Raspberry Pi is named gesture that tracks an object (a finger) with features pulled out. The main purpose of a gesture recognition system is to establish a connection between a human and a computer control system. Camera is used in this system and it captures the various gestures of hands. Various algorithms are taking place in processing of image. First preprocessing of the image takes place. Finally, the sign is identified by using Tensor flow algorithm and the outcome result as a voice using TTS algorithm. Open CV Python is implemented in this system. Various libraries are used in this system.","PeriodicalId":186283,"journal":{"name":"2021 IEEE International Conference on Mobile Networks and Wireless Communications (ICMNWC)","volume":"64 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132517323","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}