Pub Date : 2017-05-01DOI: 10.1109/SSPS.2017.8071576
Ankur Thakur, S. Talluri, D. Saini
The theme of this paper is to present the improvement in the peak side-lobe levels (PSL) and time-bandwidth product with Chebyshev polynomial. This PSL behavior is observed by the matched filter (MF) response, which contains main-lobe width as well as side-lobes. Here to get a better reduction in the side-lobes, Chebyshev polynomials are modified by using zero-crossing there by getting the positive and negative pulse. Here two cases have been considered, in first ordinary Chebyshev polynomial are analyzed, second is a modification in the cycles of Chebyshev polynomial is incorporated. After this the smallest duration of the pulse has been used in determining the optimal duration which has the smallest mean square error (MSE) between the number of pulses incorporated and original signal. This is giving a much larger signal with less PSL by reducing the search domain considerably. This new method tries to implement a side lobe level reduction technique. All of the mentioned procedure is carried out by mathematical equations and simulation verification.
{"title":"Signal generation employing Chebyshev polynomial for pulse compression with small relative side-lobe level","authors":"Ankur Thakur, S. Talluri, D. Saini","doi":"10.1109/SSPS.2017.8071576","DOIUrl":"https://doi.org/10.1109/SSPS.2017.8071576","url":null,"abstract":"The theme of this paper is to present the improvement in the peak side-lobe levels (PSL) and time-bandwidth product with Chebyshev polynomial. This PSL behavior is observed by the matched filter (MF) response, which contains main-lobe width as well as side-lobes. Here to get a better reduction in the side-lobes, Chebyshev polynomials are modified by using zero-crossing there by getting the positive and negative pulse. Here two cases have been considered, in first ordinary Chebyshev polynomial are analyzed, second is a modification in the cycles of Chebyshev polynomial is incorporated. After this the smallest duration of the pulse has been used in determining the optimal duration which has the smallest mean square error (MSE) between the number of pulses incorporated and original signal. This is giving a much larger signal with less PSL by reducing the search domain considerably. This new method tries to implement a side lobe level reduction technique. All of the mentioned procedure is carried out by mathematical equations and simulation verification.","PeriodicalId":382353,"journal":{"name":"2017 Third International Conference on Sensing, Signal Processing and Security (ICSSS)","volume":"448 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116432861","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 : 2017-05-01DOI: 10.1109/SSPS.2017.8071618
A.M. Ezhilazhahi, P. Bhuvaneswari
In recent years, the increasing demand on organic farming necessitates continuous monitoring of plant health. In order to ensure the quality and quantity this becomes more essential. Hence, the objective of this research is to develop a remote monitoring system that continuously monitors the soil moisture of the plant. The Wireless Sensor Network (WSN) is integrated with Internet of Things (IoT) to achieve the above objective. Further, to enhance the network lifetime, Exponential Weighted Moving Average (EWMA) event detection algorithm is adopted in the proposed research.
{"title":"IoT enabled plant soil moisture monitoring using wireless sensor networks","authors":"A.M. Ezhilazhahi, P. Bhuvaneswari","doi":"10.1109/SSPS.2017.8071618","DOIUrl":"https://doi.org/10.1109/SSPS.2017.8071618","url":null,"abstract":"In recent years, the increasing demand on organic farming necessitates continuous monitoring of plant health. In order to ensure the quality and quantity this becomes more essential. Hence, the objective of this research is to develop a remote monitoring system that continuously monitors the soil moisture of the plant. The Wireless Sensor Network (WSN) is integrated with Internet of Things (IoT) to achieve the above objective. Further, to enhance the network lifetime, Exponential Weighted Moving Average (EWMA) event detection algorithm is adopted in the proposed research.","PeriodicalId":382353,"journal":{"name":"2017 Third International Conference on Sensing, Signal Processing and Security (ICSSS)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123645927","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 : 2017-05-01DOI: 10.1109/SSPS.2017.8071598
Abhishek Kumar, P. Babu, N. Babu, Saptarshi Roy
A second order Taylor-Kalman-Fourier (T2KF) filter based backup protection of teed-transmission network is demonstrated in this paper. The measured current and voltage signals at relaying end will be supplied to the proposed T2KF filter to estimation of the faulty section from relaying point. This algorithm has considered the out-feeding effect in the presence of practical load for estimating the fault impedance accurately. The proposed method is tested on a teed-transmission network. The results show that this method has identified the faults in backup zones successfully.
{"title":"A back-up protection of teed-transmission line using Taylor-Kalman-Fourier filter","authors":"Abhishek Kumar, P. Babu, N. Babu, Saptarshi Roy","doi":"10.1109/SSPS.2017.8071598","DOIUrl":"https://doi.org/10.1109/SSPS.2017.8071598","url":null,"abstract":"A second order Taylor-Kalman-Fourier (T2KF) filter based backup protection of teed-transmission network is demonstrated in this paper. The measured current and voltage signals at relaying end will be supplied to the proposed T2KF filter to estimation of the faulty section from relaying point. This algorithm has considered the out-feeding effect in the presence of practical load for estimating the fault impedance accurately. The proposed method is tested on a teed-transmission network. The results show that this method has identified the faults in backup zones successfully.","PeriodicalId":382353,"journal":{"name":"2017 Third International Conference on Sensing, Signal Processing and Security (ICSSS)","volume":"62 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124734007","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 : 2017-05-01DOI: 10.1109/SSPS.2017.8071613
T. Kumar, K. Rashmi, Sreevidhya Ramadoss, L. K. Sandhya, T. J. Sangeetha
Magnetic Resonance Imaging is a standard non-invasive methodology used in medical field for the analysis, diagnosis and treatment of brain tissues. The early diagnosis of brain tumor helps in saving the patients' life by providing proper treatment. The accurate detection of tumors in the MRI slices becomes a fastidious task to perform and therefore, by this proposed system, the classification and segmentation the tumor region can be done accurately. Segmentation and 3D reconstruction also uses the detection of tumor from an MR image. The manual tracing and visual exploration by doctors will be restrained in order to avoid time consumption. The brain tumor detection allows localizing a mass of abnormal cells in a slice of Magnetic Resonance (MR) using SVM Classifier and segmentation of the tumor cells to know about the size of the tumor present in that segmented area. The extracted features of the segmented portion will be trained using artificial neural network to display the type of the tumor. These features will also be used for comparing the accuracy of different classifiers in Classification learner app. The scope of this project is helpful in post processing of the extracted region like the tumor segmentation.
{"title":"Brain tumor detection using SVM classifier","authors":"T. Kumar, K. Rashmi, Sreevidhya Ramadoss, L. K. Sandhya, T. J. Sangeetha","doi":"10.1109/SSPS.2017.8071613","DOIUrl":"https://doi.org/10.1109/SSPS.2017.8071613","url":null,"abstract":"Magnetic Resonance Imaging is a standard non-invasive methodology used in medical field for the analysis, diagnosis and treatment of brain tissues. The early diagnosis of brain tumor helps in saving the patients' life by providing proper treatment. The accurate detection of tumors in the MRI slices becomes a fastidious task to perform and therefore, by this proposed system, the classification and segmentation the tumor region can be done accurately. Segmentation and 3D reconstruction also uses the detection of tumor from an MR image. The manual tracing and visual exploration by doctors will be restrained in order to avoid time consumption. The brain tumor detection allows localizing a mass of abnormal cells in a slice of Magnetic Resonance (MR) using SVM Classifier and segmentation of the tumor cells to know about the size of the tumor present in that segmented area. The extracted features of the segmented portion will be trained using artificial neural network to display the type of the tumor. These features will also be used for comparing the accuracy of different classifiers in Classification learner app. The scope of this project is helpful in post processing of the extracted region like the tumor segmentation.","PeriodicalId":382353,"journal":{"name":"2017 Third International Conference on Sensing, Signal Processing and Security (ICSSS)","volume":"101 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129371055","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 : 2017-05-01DOI: 10.1109/SSPS.2017.8071556
K. Sriraghav, N. Vidya, G. Varshitha, S. Jayanthi, K. R. S. Chandran
The Internet of Things (IoT) is spanning into the most diverse, widespread and pervasive global network of all. In IoT applications, enormous amounts of heterogeneous and unstructured data are continuously generated on an unprecedented scale. The data sensed is sent across the network which increases the network traffic. Retrieving the data in an efficient and economical way is also a challenge. The paper proposes clustered-tier architecture, where sensors are clustered based on their geographical area and controlled by a secondary controller. The sensors can communicate only to the secondary controller while the secondary controllers are connected to the sink. There is assumed to be no sensor-sensor communication. Dynamic relocation of sensors is also addressed. For an environmental monitoring system, the proposed system reduces the network traffic on an average by 58% compared to existing distributive sensing search techniques for IoT.
{"title":"Sub-system model for data collection and distributed sensing search technique for Internet of Things applications","authors":"K. Sriraghav, N. Vidya, G. Varshitha, S. Jayanthi, K. R. S. Chandran","doi":"10.1109/SSPS.2017.8071556","DOIUrl":"https://doi.org/10.1109/SSPS.2017.8071556","url":null,"abstract":"The Internet of Things (IoT) is spanning into the most diverse, widespread and pervasive global network of all. In IoT applications, enormous amounts of heterogeneous and unstructured data are continuously generated on an unprecedented scale. The data sensed is sent across the network which increases the network traffic. Retrieving the data in an efficient and economical way is also a challenge. The paper proposes clustered-tier architecture, where sensors are clustered based on their geographical area and controlled by a secondary controller. The sensors can communicate only to the secondary controller while the secondary controllers are connected to the sink. There is assumed to be no sensor-sensor communication. Dynamic relocation of sensors is also addressed. For an environmental monitoring system, the proposed system reduces the network traffic on an average by 58% compared to existing distributive sensing search techniques for IoT.","PeriodicalId":382353,"journal":{"name":"2017 Third International Conference on Sensing, Signal Processing and Security (ICSSS)","volume":"250 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122373159","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 : 2017-05-01DOI: 10.1109/SSPS.2017.8071575
K. Arvind, B. S. Premananda, S. Yellampalli
In communication systems, the speech signal is affected by background noise which reduces perception of the received speech. In the near-end scenario, noise can't besuppressed as it is generated in real time (background) and it reaches human ear directly. Smart way is to enhance the speech samples with respect to varying background noise. This fact opens a space for developing an algorithm that would be capable of sensing the magnitude of noise and adjusting the amplitude of the speech samples according to near-end (background) noise. Based on the noise level, speech samples can be enhanced dynamically to make it more acoustic. This work focuses on averaging the gain obtained by analyzing the speech and noise energy frame-wise to obtain the smooth gain and then implementing the Near End Listening Enhancement (NELE) algorithm on DSP TMS320C6713 processor for hardware validation. The intelligibility of the unprocessed and processed speech samples is assessed using Speech Intelligibility Index (SII).
{"title":"Hardware validation for intelligibility improvement of NELE on DSP processor","authors":"K. Arvind, B. S. Premananda, S. Yellampalli","doi":"10.1109/SSPS.2017.8071575","DOIUrl":"https://doi.org/10.1109/SSPS.2017.8071575","url":null,"abstract":"In communication systems, the speech signal is affected by background noise which reduces perception of the received speech. In the near-end scenario, noise can't besuppressed as it is generated in real time (background) and it reaches human ear directly. Smart way is to enhance the speech samples with respect to varying background noise. This fact opens a space for developing an algorithm that would be capable of sensing the magnitude of noise and adjusting the amplitude of the speech samples according to near-end (background) noise. Based on the noise level, speech samples can be enhanced dynamically to make it more acoustic. This work focuses on averaging the gain obtained by analyzing the speech and noise energy frame-wise to obtain the smooth gain and then implementing the Near End Listening Enhancement (NELE) algorithm on DSP TMS320C6713 processor for hardware validation. The intelligibility of the unprocessed and processed speech samples is assessed using Speech Intelligibility Index (SII).","PeriodicalId":382353,"journal":{"name":"2017 Third International Conference on Sensing, Signal Processing and Security (ICSSS)","volume":"79 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132868078","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 : 2017-05-01DOI: 10.1109/SSPS.2017.8071638
R. Johnson
Beamforming (BF) and Blind Source Separation (BSS) have similar goals in terms of signal separation. Combining both these techniques to overcome the drawbacks faced in both the processes is always an interesting task. BSS suffers a serious issue of permutation ambiguity which can be solved by combining it with BF. While combining both BSS and BF, Short Time Fourier Transform (STFT) is used in order to have the information about the signal's frequency content and the variations of its content over time since all the time related information is lost while we deal the BSS problem in frequency domain. The window length in STFT has a serious effect on the Signal to Interference Ratio (SIR) while the separation of signal is done. The result is tested in a free field environment with two speech sources.
{"title":"Effect of window length in combining blind source separation and beamforming","authors":"R. Johnson","doi":"10.1109/SSPS.2017.8071638","DOIUrl":"https://doi.org/10.1109/SSPS.2017.8071638","url":null,"abstract":"Beamforming (BF) and Blind Source Separation (BSS) have similar goals in terms of signal separation. Combining both these techniques to overcome the drawbacks faced in both the processes is always an interesting task. BSS suffers a serious issue of permutation ambiguity which can be solved by combining it with BF. While combining both BSS and BF, Short Time Fourier Transform (STFT) is used in order to have the information about the signal's frequency content and the variations of its content over time since all the time related information is lost while we deal the BSS problem in frequency domain. The window length in STFT has a serious effect on the Signal to Interference Ratio (SIR) while the separation of signal is done. The result is tested in a free field environment with two speech sources.","PeriodicalId":382353,"journal":{"name":"2017 Third International Conference on Sensing, Signal Processing and Security (ICSSS)","volume":"56 4","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132949762","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 : 2017-05-01DOI: 10.1109/SSPS.2017.8071591
Soumya Ranjan Moharana, V. Jha, Anurag Satpathy, S. K. Addya, A. K. Turuk, B. Majhi
Internet of Things (IoT) cloud networks is itself a pervasive idea where all the physical objects are connected over the internet and are allocated with special self-identifying ability to discover other potential objects to transmit data over the internet. The most important shortcoming of IoT cloud networks which needs immediate addressing is the issue of IoT nodes when used within a virtual network of a cloud system. The IoT nodes often communicate over a virtual network and this communication needs to be monitored and managed by the cloud service provider (CSP). This CSP needs to make sure that no IoT node with malicious intent can thrive in such a network. In this paper we propose a framework for the security over virtual network for IoT nodes in a cloud system. Firstly, we propose a secure key management protocol between the CSP and the user group having the IoT nodes using a balanced incomplete block design (BIBD) model. Secondly, we device a lightweight cryptographic technique involving a key exchange protocol to establish a secure end-to-end communication between the IoT nodes. Finally we measure the efficiency and resiliency of the distribution using different metrics.
{"title":"Secure key-distribution in IoT cloud networks","authors":"Soumya Ranjan Moharana, V. Jha, Anurag Satpathy, S. K. Addya, A. K. Turuk, B. Majhi","doi":"10.1109/SSPS.2017.8071591","DOIUrl":"https://doi.org/10.1109/SSPS.2017.8071591","url":null,"abstract":"Internet of Things (IoT) cloud networks is itself a pervasive idea where all the physical objects are connected over the internet and are allocated with special self-identifying ability to discover other potential objects to transmit data over the internet. The most important shortcoming of IoT cloud networks which needs immediate addressing is the issue of IoT nodes when used within a virtual network of a cloud system. The IoT nodes often communicate over a virtual network and this communication needs to be monitored and managed by the cloud service provider (CSP). This CSP needs to make sure that no IoT node with malicious intent can thrive in such a network. In this paper we propose a framework for the security over virtual network for IoT nodes in a cloud system. Firstly, we propose a secure key management protocol between the CSP and the user group having the IoT nodes using a balanced incomplete block design (BIBD) model. Secondly, we device a lightweight cryptographic technique involving a key exchange protocol to establish a secure end-to-end communication between the IoT nodes. Finally we measure the efficiency and resiliency of the distribution using different metrics.","PeriodicalId":382353,"journal":{"name":"2017 Third International Conference on Sensing, Signal Processing and Security (ICSSS)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127900587","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 : 2017-05-01DOI: 10.1109/SSPS.2017.8071607
S. Gogula Krishnan, T. Inbarasan, P. Chitra
The congestion in on-chip networks is a major factor that degrades the performance due to increased message latency. In this paper, we present a hybrid routing scheme based on the reinforcement learning method, Q-leaning and odd-even turn model for 2-D mesh topology. This approach restricts the locations where some turns can be taken so that deadlock is avoided and also avoids congestion by considering the latency related information stored in the routing table. This hybrid Odd even Q routing (HOEQ) approach results in better routing decision and turns out to be more reliable. Experimental results show that the proposed approach performs better for given traffic patterns.
{"title":"Hybrid adaptive routing algorithm for 2D mesh on-chip networks","authors":"S. Gogula Krishnan, T. Inbarasan, P. Chitra","doi":"10.1109/SSPS.2017.8071607","DOIUrl":"https://doi.org/10.1109/SSPS.2017.8071607","url":null,"abstract":"The congestion in on-chip networks is a major factor that degrades the performance due to increased message latency. In this paper, we present a hybrid routing scheme based on the reinforcement learning method, Q-leaning and odd-even turn model for 2-D mesh topology. This approach restricts the locations where some turns can be taken so that deadlock is avoided and also avoids congestion by considering the latency related information stored in the routing table. This hybrid Odd even Q routing (HOEQ) approach results in better routing decision and turns out to be more reliable. Experimental results show that the proposed approach performs better for given traffic patterns.","PeriodicalId":382353,"journal":{"name":"2017 Third International Conference on Sensing, Signal Processing and Security (ICSSS)","volume":"70 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127993347","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 : 2017-05-01DOI: 10.1109/SSPS.2017.8071592
Jaymala Dave, Sagar Gondaliya, Bhumi Patel, A. Mascarenhas, Maya Varghese
In RFID based system, the details of the products are displayed on the LCD screen which is attached to the cart/trolley as the products are dropped in to the trolley and at the end of shopping the customers pays the bill shown on the LCD screen and conform their payment. The recommended system goals to switch heavy basket/cart with smartphones. Smartphones come with a prebuilt NFC reader/writer. These readers can read NFC tags. In the shopping centre, each product would have 1 NFC tag that holds whole information about that product. Customer can touch or wave their mobile on NFC tag and add/remove the product to/from the trolley on their mobile. There is no want to carry the trolley/physical cart. At the merchant's end, there would be a system for billing where customer would scan their smartphone and transfer the product particulars for billing. This way the system reduces the physical task by customer load effectively. The Range of NFC is 4–10 cm (compared to RFID is 1.5 cm), cost of NFC system is inexpensive than RFID, Avg processing time of NFC is 0.98(compared to RFID is 0.99). Both NFC and RFID having similar status scenario (Complete listings of the products, Automatic billing, Update inventory in the central system).
{"title":"M-commerce shopping using NFC","authors":"Jaymala Dave, Sagar Gondaliya, Bhumi Patel, A. Mascarenhas, Maya Varghese","doi":"10.1109/SSPS.2017.8071592","DOIUrl":"https://doi.org/10.1109/SSPS.2017.8071592","url":null,"abstract":"In RFID based system, the details of the products are displayed on the LCD screen which is attached to the cart/trolley as the products are dropped in to the trolley and at the end of shopping the customers pays the bill shown on the LCD screen and conform their payment. The recommended system goals to switch heavy basket/cart with smartphones. Smartphones come with a prebuilt NFC reader/writer. These readers can read NFC tags. In the shopping centre, each product would have 1 NFC tag that holds whole information about that product. Customer can touch or wave their mobile on NFC tag and add/remove the product to/from the trolley on their mobile. There is no want to carry the trolley/physical cart. At the merchant's end, there would be a system for billing where customer would scan their smartphone and transfer the product particulars for billing. This way the system reduces the physical task by customer load effectively. The Range of NFC is 4–10 cm (compared to RFID is 1.5 cm), cost of NFC system is inexpensive than RFID, Avg processing time of NFC is 0.98(compared to RFID is 0.99). Both NFC and RFID having similar status scenario (Complete listings of the products, Automatic billing, Update inventory in the central system).","PeriodicalId":382353,"journal":{"name":"2017 Third International Conference on Sensing, Signal Processing and Security (ICSSS)","volume":"817 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123289246","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：