Pub Date : 2020-07-01DOI: 10.1109/ICCSP48568.2020.9182067
K. Sathya, J. Premalatha, S. Suwathika
In the past decade, the Machine Learning (ML) and Deep learning (DL) has produced much research interest in the society and attracted them. Now-a-days, the Internet and social life make a lead in most of their life but it has serious social threats. It is a challenging thing to protect the sensitive information, data network and the computers which are in unauthorized cyber-attacks. For protecting the data’s we need the cyber security. For these problems, the recent technologies of Deep learning and Machine Learning are integrated with the cyber-attacks to provide the solution for the problems. This paper gives a synopsis of utilizing deep learning to enhance the security of cyber world and various challenges in integrating deep learning into cyber security are analyzed.
{"title":"Reinforcing Cyber World Security with Deep Learning Approaches","authors":"K. Sathya, J. Premalatha, S. Suwathika","doi":"10.1109/ICCSP48568.2020.9182067","DOIUrl":"https://doi.org/10.1109/ICCSP48568.2020.9182067","url":null,"abstract":"In the past decade, the Machine Learning (ML) and Deep learning (DL) has produced much research interest in the society and attracted them. Now-a-days, the Internet and social life make a lead in most of their life but it has serious social threats. It is a challenging thing to protect the sensitive information, data network and the computers which are in unauthorized cyber-attacks. For protecting the data’s we need the cyber security. For these problems, the recent technologies of Deep learning and Machine Learning are integrated with the cyber-attacks to provide the solution for the problems. This paper gives a synopsis of utilizing deep learning to enhance the security of cyber world and various challenges in integrating deep learning into cyber security are analyzed.","PeriodicalId":321133,"journal":{"name":"2020 International Conference on Communication and Signal Processing (ICCSP)","volume":"97 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131987250","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}
Pub Date : 2020-07-01DOI: 10.1109/ICCSP48568.2020.9182110
Sayantani Ghosh, Mousumi Laha, A. Konar
This paper intends to develop a novel methodology that helps to determine the variation of pain perception across various individuals using EEG signal analysis. Three types of touch stimuli: heat, bristles and pinch with varying intensity levels are utilized for the experiment. The brain signals acquired are analyzed using eLORETA software that confirms the involvement of frontal and parietal lobes for this cognitive activity. Additionally, frequency analysis undertaken infers the participation of alpha and theta bands for the said task. The signals are further evaluated to inspect the existence of any Event Related Potential (ERP) signal. A unique and notable ERP signal has been found when a subject finds the perceived stimuli to be painful. However, no relevant ERP component is generated when the subject finds the presented stimuli to be completely painless. A novel Interval Type-2 fuzzy classifier has been designed to classify these two distinct conditions (painful and non-painful). Performance analysis undertaken confirms the superlative behaviour of the proposed classifier with respect to other standard ones. Moreover, statistical evaluation also assures the superior performance of the proposed classifier model. Hence, this method can act as a neuronal marker to detect an individual’s pain sensitivity that can be used to diagnose and treat various neurological disorders and chronic pain based diseases.
{"title":"P1000 Induced Brain Signal Analysis for Assessing Subjective Pain Sensitivity using Type-2 Fuzzy Classifier","authors":"Sayantani Ghosh, Mousumi Laha, A. Konar","doi":"10.1109/ICCSP48568.2020.9182110","DOIUrl":"https://doi.org/10.1109/ICCSP48568.2020.9182110","url":null,"abstract":"This paper intends to develop a novel methodology that helps to determine the variation of pain perception across various individuals using EEG signal analysis. Three types of touch stimuli: heat, bristles and pinch with varying intensity levels are utilized for the experiment. The brain signals acquired are analyzed using eLORETA software that confirms the involvement of frontal and parietal lobes for this cognitive activity. Additionally, frequency analysis undertaken infers the participation of alpha and theta bands for the said task. The signals are further evaluated to inspect the existence of any Event Related Potential (ERP) signal. A unique and notable ERP signal has been found when a subject finds the perceived stimuli to be painful. However, no relevant ERP component is generated when the subject finds the presented stimuli to be completely painless. A novel Interval Type-2 fuzzy classifier has been designed to classify these two distinct conditions (painful and non-painful). Performance analysis undertaken confirms the superlative behaviour of the proposed classifier with respect to other standard ones. Moreover, statistical evaluation also assures the superior performance of the proposed classifier model. Hence, this method can act as a neuronal marker to detect an individual’s pain sensitivity that can be used to diagnose and treat various neurological disorders and chronic pain based diseases.","PeriodicalId":321133,"journal":{"name":"2020 International Conference on Communication and Signal Processing (ICCSP)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134337986","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}
Pub Date : 2020-07-01DOI: 10.1109/ICCSP48568.2020.9182185
N. Geetha, D. Harinee Devi., S. Samyuktha, M. Vishnu
The cyberspace news consumption is increasing day by day all over the world. The main reason for cyber space news consumption is due to its rapid spread of information and its easy access which lead people to consume news rapidly without the knowledge of whether the news is false or true. Thus, it leads to the wide spread of false news which leads to the negative impacts on society. Therefore false news prediction on cyberspace is attracting a tremendous attention. The issue of fake-news prediction on cyberspace is both challenging and relevant as spreading of fake news occurs in various streams like text, audio, video, images etc. This model works on processing the text and images together by providing an interactive Application Interface (API), i.e. text by applying the model Logistic regression classifier and image by applying self-consistency algorithm. The natural language tool kit (NLTK) model is used for these implementation through python. Once the news is predicted fake, a report is redirected to the authorized website (cybercrime department) to take the immediate necessary actions required to stop these news from spreading.
{"title":"Cyberspace News Prediction of Text and Image with Report Generation","authors":"N. Geetha, D. Harinee Devi., S. Samyuktha, M. Vishnu","doi":"10.1109/ICCSP48568.2020.9182185","DOIUrl":"https://doi.org/10.1109/ICCSP48568.2020.9182185","url":null,"abstract":"The cyberspace news consumption is increasing day by day all over the world. The main reason for cyber space news consumption is due to its rapid spread of information and its easy access which lead people to consume news rapidly without the knowledge of whether the news is false or true. Thus, it leads to the wide spread of false news which leads to the negative impacts on society. Therefore false news prediction on cyberspace is attracting a tremendous attention. The issue of fake-news prediction on cyberspace is both challenging and relevant as spreading of fake news occurs in various streams like text, audio, video, images etc. This model works on processing the text and images together by providing an interactive Application Interface (API), i.e. text by applying the model Logistic regression classifier and image by applying self-consistency algorithm. The natural language tool kit (NLTK) model is used for these implementation through python. Once the news is predicted fake, a report is redirected to the authorized website (cybercrime department) to take the immediate necessary actions required to stop these news from spreading.","PeriodicalId":321133,"journal":{"name":"2020 International Conference on Communication and Signal Processing (ICCSP)","volume":"109 3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134467933","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}
Pub Date : 2020-07-01DOI: 10.1109/ICCSP48568.2020.9182246
T. J. V. V. P. Reddy, C. S. Kumar, K. Suman, U. Avinash, Harisudha Kuresan
The electromagnetic(EM) waves are used for long distance communication by using air as a medium but when EM waves are used for communication through soil it cannot penetrate through soil due to various compositions of soil like red, black cotton soil etc. When these waves are used for data transmission in soil there will be loss in data because of high difraction. When there is increase in transmission distance there will be high path loss and high attenuation because of interior distance. In this present day to day communication underground communication system needs to play a key role for the effective data transmission. To establish this effective wireless connection wireless underground sensor networks(WUSN) has been introduced. To overcome problems in the electromagnetic waves, Magnetic induction(MI) has been proposed as it consists of magnetic induction coils which are used as transceivers for the effective data transmission.
{"title":"Wireless Underground Sensor Network Using Magnetic Induction","authors":"T. J. V. V. P. Reddy, C. S. Kumar, K. Suman, U. Avinash, Harisudha Kuresan","doi":"10.1109/ICCSP48568.2020.9182246","DOIUrl":"https://doi.org/10.1109/ICCSP48568.2020.9182246","url":null,"abstract":"The electromagnetic(EM) waves are used for long distance communication by using air as a medium but when EM waves are used for communication through soil it cannot penetrate through soil due to various compositions of soil like red, black cotton soil etc. When these waves are used for data transmission in soil there will be loss in data because of high difraction. When there is increase in transmission distance there will be high path loss and high attenuation because of interior distance. In this present day to day communication underground communication system needs to play a key role for the effective data transmission. To establish this effective wireless connection wireless underground sensor networks(WUSN) has been introduced. To overcome problems in the electromagnetic waves, Magnetic induction(MI) has been proposed as it consists of magnetic induction coils which are used as transceivers for the effective data transmission.","PeriodicalId":321133,"journal":{"name":"2020 International Conference on Communication and Signal Processing (ICCSP)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133872417","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}
Pub Date : 2020-07-01DOI: 10.1109/ICCSP48568.2020.9182294
B. Behera, S. Varshney, M. Mohanty
In recent scenario realization of a high-capacity transmission system is one of the biggest challenges in the optical domain. Space-division multiplexing (SDM) and Mode-division multiplexing are the new age techniques those claim to establish high-speed transmission using Few-mode fibers (FMFs). FMFs have the potential to drastically improve the fiber capacity by enabling SDM and MDM. In this paper, we have proposed the design of an FMF with a compound refractive index profile to support and guide the first seven LP modes (LP01, LP11, LP12, LP02, LP21, LP31, LP41). The fiber parameters are examined to meet the design conditions to transmit seven-LP modes effectively with low bending loss, large effective-area, and a large-effective-index difference (Δn-eff) between the LP-modes to limit the mode coupling between the spatial modes for weakly-coupled MDM transmission.
{"title":"Design of Seven-LP-Mode Compound-Index Few-Mode-Fiber for Mode-Division-Multiplexing Transmission","authors":"B. Behera, S. Varshney, M. Mohanty","doi":"10.1109/ICCSP48568.2020.9182294","DOIUrl":"https://doi.org/10.1109/ICCSP48568.2020.9182294","url":null,"abstract":"In recent scenario realization of a high-capacity transmission system is one of the biggest challenges in the optical domain. Space-division multiplexing (SDM) and Mode-division multiplexing are the new age techniques those claim to establish high-speed transmission using Few-mode fibers (FMFs). FMFs have the potential to drastically improve the fiber capacity by enabling SDM and MDM. In this paper, we have proposed the design of an FMF with a compound refractive index profile to support and guide the first seven LP modes (LP01, LP11, LP12, LP02, LP21, LP31, LP41). The fiber parameters are examined to meet the design conditions to transmit seven-LP modes effectively with low bending loss, large effective-area, and a large-effective-index difference (Δn-eff) between the LP-modes to limit the mode coupling between the spatial modes for weakly-coupled MDM transmission.","PeriodicalId":321133,"journal":{"name":"2020 International Conference on Communication and Signal Processing (ICCSP)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123128228","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}
Over the last few decades, the quality of air has been deteriorating at an alarming rate leading to demise of nearly seven million people annually worldwide. In the midst of the above worrisome facts citizens across the globe deserve transparency about the quality of the environment they live in, so that appropriate decisions could be taken before it is too late. Keeping this in mind a prototype for an air quality monitoring system has been developed in this work. The proposed air quality monitoring device comprises of a NodeMCU ESP32, a MQ-135 gas sensor and a DHT-11 temperature and humidity sensor module. As compared to other counterparts available, our proposed system gives an upper hand in terms of small size, efficient power usage and cost. The sensors record the data and send it to the NodeMCU acting as the base station of the overall setup. Having an inbuilt microcontroller and an onchip Wi-Fi transceiver, the NodeMCU not only serves the purpose of monitoring the data but also sending it to a remote server empowering tremendous scope for physical world to be communicated at a very fine and detailed level. The gas sensor records the concentration of toxic gases like NOx, CO2, benzene, smoke and gives an overall air quality parameter. If the concentration of the toxic gases exceeds a standard value an alert message is also displayed on the server. The integrated system could possibly be a big yes for the smart cities to justify steps to control pollution level in the years to follow.
{"title":"Development of an IoT-based Real-Time Air Quality Monitoring Device","authors":"Bikash Kumar Moharana, Prateek Anand, Sarvesh Kumar, Prakash Kodali","doi":"10.1109/ICCSP48568.2020.9182330","DOIUrl":"https://doi.org/10.1109/ICCSP48568.2020.9182330","url":null,"abstract":"Over the last few decades, the quality of air has been deteriorating at an alarming rate leading to demise of nearly seven million people annually worldwide. In the midst of the above worrisome facts citizens across the globe deserve transparency about the quality of the environment they live in, so that appropriate decisions could be taken before it is too late. Keeping this in mind a prototype for an air quality monitoring system has been developed in this work. The proposed air quality monitoring device comprises of a NodeMCU ESP32, a MQ-135 gas sensor and a DHT-11 temperature and humidity sensor module. As compared to other counterparts available, our proposed system gives an upper hand in terms of small size, efficient power usage and cost. The sensors record the data and send it to the NodeMCU acting as the base station of the overall setup. Having an inbuilt microcontroller and an onchip Wi-Fi transceiver, the NodeMCU not only serves the purpose of monitoring the data but also sending it to a remote server empowering tremendous scope for physical world to be communicated at a very fine and detailed level. The gas sensor records the concentration of toxic gases like NOx, CO2, benzene, smoke and gives an overall air quality parameter. If the concentration of the toxic gases exceeds a standard value an alert message is also displayed on the server. The integrated system could possibly be a big yes for the smart cities to justify steps to control pollution level in the years to follow.","PeriodicalId":321133,"journal":{"name":"2020 International Conference on Communication and Signal Processing (ICCSP)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129137577","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}
Pub Date : 2020-07-01DOI: 10.1109/ICCSP48568.2020.9182065
Pradeep Kumar Mugithe, Rohit Varma Mudunuri, B. Rajasekar, S. Karthikeyan
Farming is the foundation of Indian economy. In recent years, crop yield is not as expected because the plants are drastically affected by diseases. Hence the farmer has to apply the pesticides for the entire farm periodically. It not only results in wastage of manpower, money and time, but also in increase of toxic levels in vegetables. Consuming such vegetables effects both animal and human life. Hence it is necessary to obtain a balance between high yield and less toxic vegetables. It is possible only when pesticides are applied to disease affected plants. Owing to the large size of the farm, manual inspection is not possible. Hence it is necessary to develop an automated disease detecting and alerting system. The proposed system aims at developing image processing technique for disease detection and alerting. Steps involved in this are image acquisition, image processing, image segmentation, feature extraction, classification and disease categorization. After detecting the disease, it sends the alerts through the buzzer.
{"title":"Image Processing Technique for Automatic Detection of Plant Diseases and Alerting System in Agricultural Farms","authors":"Pradeep Kumar Mugithe, Rohit Varma Mudunuri, B. Rajasekar, S. Karthikeyan","doi":"10.1109/ICCSP48568.2020.9182065","DOIUrl":"https://doi.org/10.1109/ICCSP48568.2020.9182065","url":null,"abstract":"Farming is the foundation of Indian economy. In recent years, crop yield is not as expected because the plants are drastically affected by diseases. Hence the farmer has to apply the pesticides for the entire farm periodically. It not only results in wastage of manpower, money and time, but also in increase of toxic levels in vegetables. Consuming such vegetables effects both animal and human life. Hence it is necessary to obtain a balance between high yield and less toxic vegetables. It is possible only when pesticides are applied to disease affected plants. Owing to the large size of the farm, manual inspection is not possible. Hence it is necessary to develop an automated disease detecting and alerting system. The proposed system aims at developing image processing technique for disease detection and alerting. Steps involved in this are image acquisition, image processing, image segmentation, feature extraction, classification and disease categorization. After detecting the disease, it sends the alerts through the buzzer.","PeriodicalId":321133,"journal":{"name":"2020 International Conference on Communication and Signal Processing (ICCSP)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132516466","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}
Pub Date : 2020-07-01DOI: 10.1109/ICCSP48568.2020.9182135
K.A. Karthigeyan, S. Radha
This paper presents a current reuse oscillator designed for 5G millimeter band frequencies. The designed was VCO simulated with low-Q inductor on-chip CMOS integration. The oscillator generates a signal of 440mV amplitude running at 27. 7S GHz with the phase noise of -102.5dBc and 550 mV amplitude running at 40 GHz with the phase noise of-103.6 dBc at lMHz carrier offset. The oscillator circuit designed from a 1V supply drawing bias currents of 1.5 mA and 1 mA DC current for the lowest and highest frequency band operation.
{"title":"Current Reuse Oscillator Design for 5G Mobile Application using 90nm CMOS","authors":"K.A. Karthigeyan, S. Radha","doi":"10.1109/ICCSP48568.2020.9182135","DOIUrl":"https://doi.org/10.1109/ICCSP48568.2020.9182135","url":null,"abstract":"This paper presents a current reuse oscillator designed for 5G millimeter band frequencies. The designed was VCO simulated with low-Q inductor on-chip CMOS integration. The oscillator generates a signal of 440mV amplitude running at 27. 7S GHz with the phase noise of -102.5dBc and 550 mV amplitude running at 40 GHz with the phase noise of-103.6 dBc at lMHz carrier offset. The oscillator circuit designed from a 1V supply drawing bias currents of 1.5 mA and 1 mA DC current for the lowest and highest frequency band operation.","PeriodicalId":321133,"journal":{"name":"2020 International Conference on Communication and Signal Processing (ICCSP)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133377182","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}
Pub Date : 2020-07-01DOI: 10.1109/ICCSP48568.2020.9182225
Soumya S Pillai, R. K. Megalingam
Medical imaging or processing involves a wide range of computations on which the accuracy of analysis depends on the most. So to enhance the accuracy of analysis we need to reduce the computational geometric problems. Usually problems occur during the image segmentation or shape approximation or 3D modeling, and volumetric data registration. Con-formal geometric algebra is an effective paradigm to all this problems. The images we obtain after the MRI scan is 2D image from which the tumor has to be identified. This paper provides a key to identify the growth of the tumor in the regions inside the brain and to develop a 3D modeling of the tumor for the future reference which may help the doctor in the treatment of the tumor affected patient effectively. For the accurate prediction of whether a tumor is there in the brain related regions or not 2D image obtained must be first taken for the noise removal.
{"title":"Detection and 3D Modeling of Brain Tumor using Machine learning and Conformal Geometric Algebra","authors":"Soumya S Pillai, R. K. Megalingam","doi":"10.1109/ICCSP48568.2020.9182225","DOIUrl":"https://doi.org/10.1109/ICCSP48568.2020.9182225","url":null,"abstract":"Medical imaging or processing involves a wide range of computations on which the accuracy of analysis depends on the most. So to enhance the accuracy of analysis we need to reduce the computational geometric problems. Usually problems occur during the image segmentation or shape approximation or 3D modeling, and volumetric data registration. Con-formal geometric algebra is an effective paradigm to all this problems. The images we obtain after the MRI scan is 2D image from which the tumor has to be identified. This paper provides a key to identify the growth of the tumor in the regions inside the brain and to develop a 3D modeling of the tumor for the future reference which may help the doctor in the treatment of the tumor affected patient effectively. For the accurate prediction of whether a tumor is there in the brain related regions or not 2D image obtained must be first taken for the noise removal.","PeriodicalId":321133,"journal":{"name":"2020 International Conference on Communication and Signal Processing (ICCSP)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132744799","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}
Pub Date : 2020-07-01DOI: 10.1109/ICCSP48568.2020.9182243
A. Anand, S. Nishanth, P. Vamsi Krishna, S. Krishna, T. Anjali
It is a common belief that with the advent of technology the livelihood of people in a developing community tends to get better over time. It may be true in many cases but in cases of domestic and sexual violence against women there have been no significant development. With the benefit of women, elders and basically any person who is in distress in mind and also the need for a socially centralized social network we have put forward an idea which may help curb rising crime rates by solving various issues which have been unattended by existing methodologies. Ally is a distress signal application with newer and innovative approach to solving the age old problem of rapid redressal. Existing models fail to identify the location of a person if there is no network coverage thus failing ultimately which is why we have implemented a feature to constantly track the location of a person and give the updates to guardians on an half-hourly basis. Also existing models rely on the police or the guardians to help the person in distress whereas we have taken it a step forward to crowd source help in the hour of need by sending distress signal to all nearby Ally app users within a kilometer.
{"title":"Ally - A Crowdsourced Distress Signal App","authors":"A. Anand, S. Nishanth, P. Vamsi Krishna, S. Krishna, T. Anjali","doi":"10.1109/ICCSP48568.2020.9182243","DOIUrl":"https://doi.org/10.1109/ICCSP48568.2020.9182243","url":null,"abstract":"It is a common belief that with the advent of technology the livelihood of people in a developing community tends to get better over time. It may be true in many cases but in cases of domestic and sexual violence against women there have been no significant development. With the benefit of women, elders and basically any person who is in distress in mind and also the need for a socially centralized social network we have put forward an idea which may help curb rising crime rates by solving various issues which have been unattended by existing methodologies. Ally is a distress signal application with newer and innovative approach to solving the age old problem of rapid redressal. Existing models fail to identify the location of a person if there is no network coverage thus failing ultimately which is why we have implemented a feature to constantly track the location of a person and give the updates to guardians on an half-hourly basis. Also existing models rely on the police or the guardians to help the person in distress whereas we have taken it a step forward to crowd source help in the hour of need by sending distress signal to all nearby Ally app users within a kilometer.","PeriodicalId":321133,"journal":{"name":"2020 International Conference on Communication and Signal Processing (ICCSP)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117158839","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}
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