Pub Date : 2019-07-01DOI: 10.1109/IBSSC47189.2019.8973041
Farahanaaz Shaikh, Shreya Darunde, Nikita Wahie, Swapnil G. Mali
The research aims at developing a system for hearing impaired citizens at public platforms such as railway stations, banks and bus stands, where in information transfer is crucial. Information at these platforms are generally conveyed either through text displays or audio announcements and the main drawback of conventional information broadcast is that they are not perceived by deaf people due to their inability to read or hear. In this research work, a generic sign language converter has been implemented for railway announcements in India. The corpus generation algorithm that provides the data of root words has been implemented thoroughly to provide legitimate database. For the text translation, effective and efficient use of phrase-based technique combined with rule-based translation technique has been used that yields optimum speed output thereby reducing redundancies and thus time for translation. The animated avatar has Inverse Kinematic(IK) solver tools and other rigged joints and chains which aids in movement of body parts similar to human. The sentence is translated into ASL gloss and the Web UI provides an interface which is easy to operate, it displays video of an avatar which conveys information using hand signs.
{"title":"Sign Language Translation System for Railway Station Announcements","authors":"Farahanaaz Shaikh, Shreya Darunde, Nikita Wahie, Swapnil G. Mali","doi":"10.1109/IBSSC47189.2019.8973041","DOIUrl":"https://doi.org/10.1109/IBSSC47189.2019.8973041","url":null,"abstract":"The research aims at developing a system for hearing impaired citizens at public platforms such as railway stations, banks and bus stands, where in information transfer is crucial. Information at these platforms are generally conveyed either through text displays or audio announcements and the main drawback of conventional information broadcast is that they are not perceived by deaf people due to their inability to read or hear. In this research work, a generic sign language converter has been implemented for railway announcements in India. The corpus generation algorithm that provides the data of root words has been implemented thoroughly to provide legitimate database. For the text translation, effective and efficient use of phrase-based technique combined with rule-based translation technique has been used that yields optimum speed output thereby reducing redundancies and thus time for translation. The animated avatar has Inverse Kinematic(IK) solver tools and other rigged joints and chains which aids in movement of body parts similar to human. The sentence is translated into ASL gloss and the Web UI provides an interface which is easy to operate, it displays video of an avatar which conveys information using hand signs.","PeriodicalId":148941,"journal":{"name":"2019 IEEE Bombay Section Signature Conference (IBSSC)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121890895","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 : 2019-07-01DOI: 10.1109/IBSSC47189.2019.8973051
Bhushan Patil, Sameer Pusegaonkar
On average 328,000 accidents, 109,000 injuries and 6,400 fatalities are reported annually due to drowsy driving just in the United States, making it one of the biggest factors contributing to car accidents. Despite these frightening figures, no system to solve this problem has been widely implemented. The objective of our system is to detect drowsy behavior that leads to such accidents. The system detects the eye activity of the driver and alerts him/her if drowsiness is detected. Such a system is crucial for making roads a safer place.
{"title":"Sleep Avoidance in Vehicle Ecosystem (S.A.V.E.)","authors":"Bhushan Patil, Sameer Pusegaonkar","doi":"10.1109/IBSSC47189.2019.8973051","DOIUrl":"https://doi.org/10.1109/IBSSC47189.2019.8973051","url":null,"abstract":"On average 328,000 accidents, 109,000 injuries and 6,400 fatalities are reported annually due to drowsy driving just in the United States, making it one of the biggest factors contributing to car accidents. Despite these frightening figures, no system to solve this problem has been widely implemented. The objective of our system is to detect drowsy behavior that leads to such accidents. The system detects the eye activity of the driver and alerts him/her if drowsiness is detected. Such a system is crucial for making roads a safer place.","PeriodicalId":148941,"journal":{"name":"2019 IEEE Bombay Section Signature Conference (IBSSC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130539547","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 : 2019-07-01DOI: 10.1109/IBSSC47189.2019.8972980
Sarthak Gupta, S. Bagga, Sanjay Kumar Dharandher, D. Sharma
Convolutional neural networks have been a revolution in the field of Computer Vision and are being extensively used for the purpose of image classification, object detection, generation of captions etc. CNNs are mostly considered black boxes where the internal functioning is not known. The objective of this work is to provide an explanation of the functioning of the the predictions made by the CNN. We propose a new technique for comprehending the functioning of the middle layers of the neural network and the classifier operations. The proposed approach is capable of analyzing multifarious models which are trained for applications such as object detection and recognition. In this work, probabilistic approach and gradient based approach have been used for the purpose of object localization. Geometric mean of heatmaps of both the approaches has been done. In the former approach, the true object’s gradient’s are made to flow into the last convolutional layer for the purpose of determining the most significant points which would help to predict that particular object. In the probabilistic approach, CNN’s top down attention has been used which serves the purpose of generation of attention maps which are task specific. A probabilistic scheme (to select a significant neuron in the network) has been used during backpropagation of signals from top to down in the hierarchy of network. The proposed work has been executed on CLS-LOC dataset which is a part of Imagenet dataset. The proposed work is then compared with the previously developed techniques such as saliency maps, SmoothGrad, GradCam, Top Down Neural approach to exhibit the better accuracy of the proposed work.
{"title":"GPOL: Gradient and Probabilistic approach for Object Localization to understand the working of CNNs","authors":"Sarthak Gupta, S. Bagga, Sanjay Kumar Dharandher, D. Sharma","doi":"10.1109/IBSSC47189.2019.8972980","DOIUrl":"https://doi.org/10.1109/IBSSC47189.2019.8972980","url":null,"abstract":"Convolutional neural networks have been a revolution in the field of Computer Vision and are being extensively used for the purpose of image classification, object detection, generation of captions etc. CNNs are mostly considered black boxes where the internal functioning is not known. The objective of this work is to provide an explanation of the functioning of the the predictions made by the CNN. We propose a new technique for comprehending the functioning of the middle layers of the neural network and the classifier operations. The proposed approach is capable of analyzing multifarious models which are trained for applications such as object detection and recognition. In this work, probabilistic approach and gradient based approach have been used for the purpose of object localization. Geometric mean of heatmaps of both the approaches has been done. In the former approach, the true object’s gradient’s are made to flow into the last convolutional layer for the purpose of determining the most significant points which would help to predict that particular object. In the probabilistic approach, CNN’s top down attention has been used which serves the purpose of generation of attention maps which are task specific. A probabilistic scheme (to select a significant neuron in the network) has been used during backpropagation of signals from top to down in the hierarchy of network. The proposed work has been executed on CLS-LOC dataset which is a part of Imagenet dataset. The proposed work is then compared with the previously developed techniques such as saliency maps, SmoothGrad, GradCam, Top Down Neural approach to exhibit the better accuracy of the proposed work.","PeriodicalId":148941,"journal":{"name":"2019 IEEE Bombay Section Signature Conference (IBSSC)","volume":"104 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124035893","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 : 2019-07-01DOI: 10.1109/IBSSC47189.2019.8973077
Niraj Bagh, T. J. Reddy, M. Reddy
In recent decades, motor imagery (MI) based brain-computer interface (BCI) is acting as a rehabilitation tool for motor disabled people. But it has limited applications due to its lower classification performance. To improve it, this paper introduces band power (BP) and second order difference plot (SODP) for the detection of various motor imagery (MI) activities. First, filter bank technique was implemented to the signals and sets of sub-bands were generated. The BP was evaluated for all sub-bands. To study MI activities more effectively, SODP was applied to each sub-band and area of SODP was calculated. The features (i.e. band power and area of SODP) of all sub-bands were combined and the significant features $(mathrm{p}lt 0.05)$ were extracted from one-way analysis of variance (ANOVA). The significant features were fed into multi-class support vector machine (SVM) for the decoding of MI activities. BCI competition 2008 benchmark MI dataset-II-a was used to validate the proposed technique. The performance of the proposed technique was evaluated in terms of classification accuracy (%CA), precision (P), sensitivity (S) and F1-score. The results show that the present technique improved the performance of MI based BCI system and superior to the existing methods reported in the literature.
{"title":"Classification of Motor Imagery Activities Using Band Power and Second Order Difference Plot","authors":"Niraj Bagh, T. J. Reddy, M. Reddy","doi":"10.1109/IBSSC47189.2019.8973077","DOIUrl":"https://doi.org/10.1109/IBSSC47189.2019.8973077","url":null,"abstract":"In recent decades, motor imagery (MI) based brain-computer interface (BCI) is acting as a rehabilitation tool for motor disabled people. But it has limited applications due to its lower classification performance. To improve it, this paper introduces band power (BP) and second order difference plot (SODP) for the detection of various motor imagery (MI) activities. First, filter bank technique was implemented to the signals and sets of sub-bands were generated. The BP was evaluated for all sub-bands. To study MI activities more effectively, SODP was applied to each sub-band and area of SODP was calculated. The features (i.e. band power and area of SODP) of all sub-bands were combined and the significant features $(mathrm{p}lt 0.05)$ were extracted from one-way analysis of variance (ANOVA). The significant features were fed into multi-class support vector machine (SVM) for the decoding of MI activities. BCI competition 2008 benchmark MI dataset-II-a was used to validate the proposed technique. The performance of the proposed technique was evaluated in terms of classification accuracy (%CA), precision (P), sensitivity (S) and F1-score. The results show that the present technique improved the performance of MI based BCI system and superior to the existing methods reported in the literature.","PeriodicalId":148941,"journal":{"name":"2019 IEEE Bombay Section Signature Conference (IBSSC)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121208579","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 : 2019-07-01DOI: 10.1109/IBSSC47189.2019.8973069
S. S. Tikar, Rajendra A. Patil
The objective of this paper is to develop an advanced driver assistance system with lane departure warning and forward collision warning functions with enhanced method, which will speed up the computations. In order to extract lane markings and vehicles from roadway images captured by stereo camera, the image processing methods such as coordinate systems transformation, object detection and object tracking are applied to recognize the lane markings and the vehicles. In lane marking recognition, gray scale data, dynamically changing region of interest and featured based techniques are used to detect lane markings successfully. Experimental results show that the proposed algorithm is effective in image preprocessing and can detect the lane marking and vehicle accurately with less time.
{"title":"An improved lane and vehicle detection method in Driver Assistance System with Lane Departure and Forward Collision Warning","authors":"S. S. Tikar, Rajendra A. Patil","doi":"10.1109/IBSSC47189.2019.8973069","DOIUrl":"https://doi.org/10.1109/IBSSC47189.2019.8973069","url":null,"abstract":"The objective of this paper is to develop an advanced driver assistance system with lane departure warning and forward collision warning functions with enhanced method, which will speed up the computations. In order to extract lane markings and vehicles from roadway images captured by stereo camera, the image processing methods such as coordinate systems transformation, object detection and object tracking are applied to recognize the lane markings and the vehicles. In lane marking recognition, gray scale data, dynamically changing region of interest and featured based techniques are used to detect lane markings successfully. Experimental results show that the proposed algorithm is effective in image preprocessing and can detect the lane marking and vehicle accurately with less time.","PeriodicalId":148941,"journal":{"name":"2019 IEEE Bombay Section Signature Conference (IBSSC)","volume":"214 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114846128","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 : 2019-07-01DOI: 10.1109/IBSSC47189.2019.8973055
Parmeshwar Birajadar, Meet Haria, S. G. Sangodkar, V. Gadre
There has been significant progress in the field of automatic ear recognition, wherein ear images are captured in a constrained environment. But unconstrained ear recognition have acquired less attention due to the unavailability of such a database having variations in illumination, pose, size, resolution and occlusions. It is a challenging pattern recognition problem due to large intra-class variability. In this paper, we propose a novel local descriptor for unconstrained ear recognition based on scattering wavelet network (ScatNet) to extract translation and small deformation invariant local features. The experiments conducted on a recently released unconstrained ear benchmark databases, such as Annotated Web Ears (AWE) and USTB-Helloear databases, and also on our newly created IIT-Bombay smartphone-captured ear database show the effectiveness and robustness of the proposed local feature descriptor in terms of Equal Error Rate (EER) and Rank-1 (R1) accuracy.
自动耳朵识别领域已经取得了重大进展，其中耳朵图像是在受限环境中捕获的。但是，由于这种数据库在光照、姿态、大小、分辨率和遮挡方面存在变化，因此无约束耳识别得到的关注较少。由于类内变化很大，这是一个具有挑战性的模式识别问题。本文提出了一种基于散射小波网络(ScatNet)的无约束耳识别局部描述子，用于提取平移和小变形不变的局部特征。在最近发布的无约束耳朵基准数据库(如Annotated Web Ears (AWE)和USTB-Helloear数据库)以及我们新创建的IIT-Bombay智能手机捕获的耳朵数据库上进行的实验表明，所提出的局部特征描述符在等错误率(EER)和Rank-1 (R1)精度方面具有有效性和鲁棒性。
{"title":"Unconstrained Ear Recognition Using Deep Scattering Wavelet Network","authors":"Parmeshwar Birajadar, Meet Haria, S. G. Sangodkar, V. Gadre","doi":"10.1109/IBSSC47189.2019.8973055","DOIUrl":"https://doi.org/10.1109/IBSSC47189.2019.8973055","url":null,"abstract":"There has been significant progress in the field of automatic ear recognition, wherein ear images are captured in a constrained environment. But unconstrained ear recognition have acquired less attention due to the unavailability of such a database having variations in illumination, pose, size, resolution and occlusions. It is a challenging pattern recognition problem due to large intra-class variability. In this paper, we propose a novel local descriptor for unconstrained ear recognition based on scattering wavelet network (ScatNet) to extract translation and small deformation invariant local features. The experiments conducted on a recently released unconstrained ear benchmark databases, such as Annotated Web Ears (AWE) and USTB-Helloear databases, and also on our newly created IIT-Bombay smartphone-captured ear database show the effectiveness and robustness of the proposed local feature descriptor in terms of Equal Error Rate (EER) and Rank-1 (R1) accuracy.","PeriodicalId":148941,"journal":{"name":"2019 IEEE Bombay Section Signature Conference (IBSSC)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131047614","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 : 2019-07-01DOI: 10.1109/IBSSC47189.2019.8973040
Lopamudra Samal, P. Karuppanan, Prem Kumar, S. Sahoo
The Internet of Things (IoT) applies the sensors and MCUs on various machines, devices and equipment, and connect them through internet. This brief presents the design of a low power dynamic comparator circuit which is compatible with wide range of applications (i.e., internet of things (IoT) sensors and integrated analog to digital convertor).In this paper different types of comparator-Conventional dynamic comparator, double tail dynamic comparator and dynamic comparator with enhanced latch regeneration speed have been analyzed. Dynamic comparator with enhanced latch regeneration speed is better than previous two conventional dynamic comparator in terms of power and speed.
物联网(Internet of Things, IoT)将传感器和mcu应用于各种机器、设备和设备上，并通过互联网将它们连接起来。本简报介绍了一种低功耗动态比较器电路的设计，该电路兼容于广泛的应用(即物联网(IoT)传感器和集成模拟数字转换器)。本文分析了不同类型的比较器——常规动态比较器、双尾动态比较器和增强锁存器再生速度的动态比较器。提高锁存器再生速度的动态比较器在功率和速度上都优于前两种传统的动态比较器。
{"title":"Study and analysis of Low Power Dynamic Comparator for IOT Application","authors":"Lopamudra Samal, P. Karuppanan, Prem Kumar, S. Sahoo","doi":"10.1109/IBSSC47189.2019.8973040","DOIUrl":"https://doi.org/10.1109/IBSSC47189.2019.8973040","url":null,"abstract":"The Internet of Things (IoT) applies the sensors and MCUs on various machines, devices and equipment, and connect them through internet. This brief presents the design of a low power dynamic comparator circuit which is compatible with wide range of applications (i.e., internet of things (IoT) sensors and integrated analog to digital convertor).In this paper different types of comparator-Conventional dynamic comparator, double tail dynamic comparator and dynamic comparator with enhanced latch regeneration speed have been analyzed. Dynamic comparator with enhanced latch regeneration speed is better than previous two conventional dynamic comparator in terms of power and speed.","PeriodicalId":148941,"journal":{"name":"2019 IEEE Bombay Section Signature Conference (IBSSC)","volume":"171 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124164862","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 : 2019-07-01DOI: 10.1109/IBSSC47189.2019.8973092
D. Sawant, Vaibhavi Padwal, Jugal Joshi, Tanvi Keluskar, Ragini Lalwani, Tanushree Sharma, R. Daruwala
This paper provides a novel set of features for classification of motor imagery tasks including the following two classes: right and left hand. While performing motor imagery tasks, desynchronization is seen in the mu and betabands over the sensorimotor cortex region. In order to capture these changes in the different frequency bands, we use MEMD for decomposing the EEG into oscillatory components called IMFs which characterize either a single frequency or a narrow band of frequencies. Features are extracted by applying common spatial pattern (CSP), Entropy and Fast Walsh Hadamard Transform (FWHT) on these IMFs. Using SVM classifier, the above features yield a maximum accuracy of 95%. The proposed feature set results in a better discrimination for motor imagery signals compared to the earlier work in this field.
{"title":"Classification of Motor Imagery EEG Signals using MEMD, CSP, Entropy and Walsh Hadamard Transform","authors":"D. Sawant, Vaibhavi Padwal, Jugal Joshi, Tanvi Keluskar, Ragini Lalwani, Tanushree Sharma, R. Daruwala","doi":"10.1109/IBSSC47189.2019.8973092","DOIUrl":"https://doi.org/10.1109/IBSSC47189.2019.8973092","url":null,"abstract":"This paper provides a novel set of features for classification of motor imagery tasks including the following two classes: right and left hand. While performing motor imagery tasks, desynchronization is seen in the mu and betabands over the sensorimotor cortex region. In order to capture these changes in the different frequency bands, we use MEMD for decomposing the EEG into oscillatory components called IMFs which characterize either a single frequency or a narrow band of frequencies. Features are extracted by applying common spatial pattern (CSP), Entropy and Fast Walsh Hadamard Transform (FWHT) on these IMFs. Using SVM classifier, the above features yield a maximum accuracy of 95%. The proposed feature set results in a better discrimination for motor imagery signals compared to the earlier work in this field.","PeriodicalId":148941,"journal":{"name":"2019 IEEE Bombay Section Signature Conference (IBSSC)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127475848","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 : 2019-07-01DOI: 10.1109/IBSSC47189.2019.8972978
Arushi Anne D’souza, Priya Kaul, Eric Paul, Manali Dhuri
A Smart Mirror is a device that looks and feels like a simple mirror but is able to actively interact with the user in real time. With advancement in technology, it has now become possible to able to do a multitude of things from face recognition to voice authentication. These days the primary focus of making new technology is also ensuring their adaptability in a variety of ways. The purpose of this paper is to develop a Smart Mirror with the capability to provide weather, time, cryptocurrency, Google calendar and a greeting from the mirror in the form of a compliment. Additionally, the mirror will also be able to provide various make up effects so that users are able to view the possible outcomes of different makeup shades in the smart mirror without affecting the real face appearance in the process. Voice commands for modules implemented in the paper will also be present in place to control the modules as needed by the user. Face Recognition for notifications of a particular user will also be present. The aim here is to provide a seamless experience to the user making everyday tasks easier.
{"title":"Ambient Intelligence Using Smart Mirror-Personalized Smart Mirror for Home Use","authors":"Arushi Anne D’souza, Priya Kaul, Eric Paul, Manali Dhuri","doi":"10.1109/IBSSC47189.2019.8972978","DOIUrl":"https://doi.org/10.1109/IBSSC47189.2019.8972978","url":null,"abstract":"A Smart Mirror is a device that looks and feels like a simple mirror but is able to actively interact with the user in real time. With advancement in technology, it has now become possible to able to do a multitude of things from face recognition to voice authentication. These days the primary focus of making new technology is also ensuring their adaptability in a variety of ways. The purpose of this paper is to develop a Smart Mirror with the capability to provide weather, time, cryptocurrency, Google calendar and a greeting from the mirror in the form of a compliment. Additionally, the mirror will also be able to provide various make up effects so that users are able to view the possible outcomes of different makeup shades in the smart mirror without affecting the real face appearance in the process. Voice commands for modules implemented in the paper will also be present in place to control the modules as needed by the user. Face Recognition for notifications of a particular user will also be present. The aim here is to provide a seamless experience to the user making everyday tasks easier.","PeriodicalId":148941,"journal":{"name":"2019 IEEE Bombay Section Signature Conference (IBSSC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128883399","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 : 2019-07-01DOI: 10.1109/IBSSC47189.2019.8973089
Sahil Kalra, S. Momin, Tejas S. Kulkarni, Vaibhav Lohani
Nowadays, many cities are on the verge of becoming smart cities. A smart transportation system is at the heart of smart city but cities lag with an efficient transport system. The current public transport systems follows static routing based approach i.e. they have fixed routes and frequency irrespective of the demand. In this paper, we propose an innovative method to solve this problem by rerouting the bus on-the-go based on public demand. Public can interact, manipulate and have an effect on the routing of the buses. The interaction of the public demand with routing is enabled by a central server which will analyses all the demand data collected from booking application. To facilitate the on-demand nature, a dynamic routing algorithm has been proposed that prepares new route for buses in real time. This algorithm works in the cloud server and suggests new and more efficient routes based on the aggregated data collected. This is enabled by the city wide link of equi-important bus depots which serve as loci of control for routing and rerouting. After evaluating, the system shows tremendous performance gain in regions with highly skewed bus-demand. Further, we propose this model to be implemented in public transport systems as a 30 - 70 percent combination of static and dynamic routing respectively for easier adaptation by the commuters.
{"title":"Real Time Re-routing of Public Transportation System","authors":"Sahil Kalra, S. Momin, Tejas S. Kulkarni, Vaibhav Lohani","doi":"10.1109/IBSSC47189.2019.8973089","DOIUrl":"https://doi.org/10.1109/IBSSC47189.2019.8973089","url":null,"abstract":"Nowadays, many cities are on the verge of becoming smart cities. A smart transportation system is at the heart of smart city but cities lag with an efficient transport system. The current public transport systems follows static routing based approach i.e. they have fixed routes and frequency irrespective of the demand. In this paper, we propose an innovative method to solve this problem by rerouting the bus on-the-go based on public demand. Public can interact, manipulate and have an effect on the routing of the buses. The interaction of the public demand with routing is enabled by a central server which will analyses all the demand data collected from booking application. To facilitate the on-demand nature, a dynamic routing algorithm has been proposed that prepares new route for buses in real time. This algorithm works in the cloud server and suggests new and more efficient routes based on the aggregated data collected. This is enabled by the city wide link of equi-important bus depots which serve as loci of control for routing and rerouting. After evaluating, the system shows tremendous performance gain in regions with highly skewed bus-demand. Further, we propose this model to be implemented in public transport systems as a 30 - 70 percent combination of static and dynamic routing respectively for easier adaptation by the commuters.","PeriodicalId":148941,"journal":{"name":"2019 IEEE Bombay Section Signature Conference (IBSSC)","volume":"439 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125244208","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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