{"title":"Real-Time Forward Collision Alert System using Raspberry Pi","authors":"Wai Chun Phoon, P. Lau","doi":"10.1109/ISPACS48206.2019.8986282","DOIUrl":"https://doi.org/10.1109/ISPACS48206.2019.8986282","url":null,"abstract":"Most new luxury cars often comes with some form of driving assistance systems to reduce the risk of car accidents - such as the lane departure warning system, automatic parking, anti-lock braking system(ABS), blind spot monitor and forward collision warning system. These systems are developed to enhance the car safety and to provide a safer driving conditions. Due to its cost and design, these systems, often are only available in luxury cars. The main purpose of this work is to propose a real-time low-cost Forward Collision Alert System (FCAS). The FCAS are able to alert drivers, when their cars are getting too close to the front vehicle by estimating the speed of the car in front, using a loud beeping sound. The FCAS is then embedded onto a Raspberry Pi for real-time. Experimental results shows that the system can reliably alert the driver, in real-time, when a moving vehicle in front position is too close.","PeriodicalId":6765,"journal":{"name":"2019 International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS)","volume":"20 1","pages":"1-2"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87507152","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":"Performance Analysis of Power Outage Probability for Drone based IoT Connectivity Network","authors":"S. Duangsuwan, Anna Chusongsang, S. Promwong","doi":"10.1109/ISPACS48206.2019.8986314","DOIUrl":"https://doi.org/10.1109/ISPACS48206.2019.8986314","url":null,"abstract":"In this paper, we present a performance analysis of power outage probability of using on drone communicated with an internet of things (IoT) connectivity network. We obtain that there are several IoT devices are connected with a drone as simultaneously. Therefore, the power outage probability (POP) is analyzed based on the verifying of drone height which ensures the best performance in term of connectivity network. Experimental results confirm that this analysis is very useful for drone usage as drone small cell or hot-spot to distribute the transmitting power to coverage all IoT devices.","PeriodicalId":6765,"journal":{"name":"2019 International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS)","volume":"10 1","pages":"1-4"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82362200","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":"Function Block-Based Robust Firmware Update Technique for Additional Flash-Area/Energy-Consumption Overhead Reduction","authors":"Jisu Kwon, Jeonghun Cho, Daejin Park","doi":"10.1109/ISPACS48206.2019.8986373","DOIUrl":"https://doi.org/10.1109/ISPACS48206.2019.8986373","url":null,"abstract":"Energy consumption and flash-memory usage are very limited in microcontrollers that make up the sensor network, accordingly, the process of updating the embedded firmware should also be low cost and energy efficient. This work proposes a technique that overcomes limitations due to increased costs of configuring the sensor network by additional memory usages and increased energy consumption resulting from firmware updates. Instead of dealing with the whole firmware, we split the firmware into function blocks and managed them with a function map that indicate each function block address. Further, by only updating function blocks where differences exist, we successfully reduced flash memory usage and energy consumption that occurred during the firmware update process. We implemented the proposed technique with the target measurement environment, and the result shows that maximum flash memory usage reduced by 91.4% and that 71.4% reduction in execution time resulted in a 69% reduction in energy consumption over the conventional method.","PeriodicalId":6765,"journal":{"name":"2019 International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS)","volume":"89 1","pages":"1-2"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73023962","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":"The regression model of NOx emission in a real driving automobile","authors":"Hung-Ta Wen, Ming-An Li, Jau-Huai Lu","doi":"10.1109/ISPACS48206.2019.8986392","DOIUrl":"https://doi.org/10.1109/ISPACS48206.2019.8986392","url":null,"abstract":"Although the Portable Emission Measurement System (PEMS) has become the official certification procedure for vehicles, but it is very expensive and cannot be used as a monitoring device for massive use. The purpose of this study is to establish a low-cost vehicle pollution monitoring system (NGK NOx sensor, Arduino with CanBus) and uses this system to measure the actual vehicle road pollution emissions. In addition, proposes an ANN nonlinear autoregressive exogenous model (NARX) to predict NOx emissions.","PeriodicalId":6765,"journal":{"name":"2019 International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS)","volume":"9 1","pages":"1-2"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77642561","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 Efficient Speech Recognition Algorithm for Small Intelligent Electronic Devices","authors":"Zhichao Zheng, Xiaotao Lin, Weiwei Zhang, Jianqing Zhu, Huanqiang Zeng","doi":"10.1109/ISPACS48206.2019.8986399","DOIUrl":"https://doi.org/10.1109/ISPACS48206.2019.8986399","url":null,"abstract":"The speech recognition technology makes it possible for people to communicate with intelligent electronic devices. However, existing speech recognition algorithms are overly complex for small intelligent electronic devices (e.g., mini speakers, intelligent toys, intelligent remote controls, etc.). For this, an efficient speech recognition algorithm is proposed. Firstly, the Mel-scale Frequency Cepstral Coefficients (MFCC) is applied to extract features of voices. Secondly, the Support Vector Machines (SVM) is used to train speech classification models. Finally, a speech database is collected to validate the proposed algorithm. The speech database contains 500 audio files of 10 speech commands for an electric motor car driving assistant and 550 audio files of 11 speech commands for a intelligent remote control. The proposed method is evaluated via a 5-fold cross-validation, and experiments show that the propose method acquires 94.20% and 88.73% average accuracy rates for the electric motor car driving assistant and the intelligent remote control, respectively.","PeriodicalId":6765,"journal":{"name":"2019 International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS)","volume":"57 1","pages":"1-2"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73581433","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}
Tien-Ying Kuo, Yu-Jen Wei, Ming-Jui Lee, Tzu-Hao Lin
{"title":"Automatic Damage Recovery of Old Photos Based on Convolutional Neural Network","authors":"Tien-Ying Kuo, Yu-Jen Wei, Ming-Jui Lee, Tzu-Hao Lin","doi":"10.1109/ISPACS48206.2019.8986336","DOIUrl":"https://doi.org/10.1109/ISPACS48206.2019.8986336","url":null,"abstract":"Most of the methods for repairing old photos today are to manually process them using image editing software, such as Photoshop. The time of manual repairing is directly proportional to the damage degree of the photo, which is time consuming and laborious. Therefore, this paper proposes a two-stage convolution network to automatically repair damaged old photos. The first stage will detect the damaged areas of the photos, and the second stage will repair these areas. The experiment results demonstrates our method can successfully detect and repair the damage of the photos.","PeriodicalId":6765,"journal":{"name":"2019 International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS)","volume":"63 1","pages":"1-2"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74316615","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":"Evaluation of Wireless Body Area Network Utilizing Super Orthogonal Convolutional Code","authors":"Kento Takabayashi, Hirokazu Tanaka, K. Sakakibara","doi":"10.1109/ISPACS48206.2019.8986385","DOIUrl":"https://doi.org/10.1109/ISPACS48206.2019.8986385","url":null,"abstract":"This paper provides an evaluation of IEEE 802.15.6 ultra-wideband (UWB) physical layer (PHY) based wireless body area network (WBAN) using a super orthogonal convolutional code (SOCC) as an error correcting code. Numerical results show that a low coding rate SOCC has better payload error probability performance in a constant process gain case. In addition, small delay is achieved with no retransmission in the case of a low coding rate SOCC.","PeriodicalId":6765,"journal":{"name":"2019 International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS)","volume":"25 1","pages":"1-2"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79190505","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":"Multi-Agent Deep Reinforcement Learning for Cooperative Driving in Crowded Traffic Scenarios","authors":"Jongwon Park, Kyushik Min, K. Huh","doi":"10.1109/ISPACS48206.2019.8986374","DOIUrl":"https://doi.org/10.1109/ISPACS48206.2019.8986374","url":null,"abstract":"For autonomous vehicles, lane changes on crowded roads are difficult to be performed without interactions and cooperation between vehicles. This paper proposes a novel method to learn interaction and cooperate between the multiple vehicles to solve the complex traffic problem through Multi-Agent Reinforcement Learning (MARL). The proposed network is designed based on the interaction network to learn optimal control strategies considering interaction between vehicles. By applying the proposed algorithm, the network can control and train the agents regardless of the number of agents. It is a practical advantage because the number of the vehicles is constantly changed in the real environment. The proposed method is evaluated in the connected car environment where all vehicles can exchange information with each other.","PeriodicalId":6765,"journal":{"name":"2019 International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS)","volume":"12 1","pages":"1-2"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74762297","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":"Quality Enhancement of DDBTC Decoded Image","authors":"J. W. Simatupang, Heri Prasetyo","doi":"10.1109/ISPACS48206.2019.8986362","DOIUrl":"https://doi.org/10.1109/ISPACS48206.2019.8986362","url":null,"abstract":"This paper presents two methods for improving the quality of Dot Diffused Block Truncation Coding (DDBTC) decoded image. The first method exploits the usability and effectiveness of decimated Discrete Wavelet Transform and stationary Wavelet Transform for reducing the half-toning artifact. While, the second method employs the Vector Quantization (VQ) approach for performing the image patch replacement and suppressing the unpleasant artifact of DDBTC decoded image. As documented in Experimental Section, these two methods performs well for improving the quality of DDBTC decoded image.","PeriodicalId":6765,"journal":{"name":"2019 International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS)","volume":"32 1","pages":"1-2"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75624655","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}
Guang Xing Lye, Wai-Khuen Cheng, T. Tan, C. Hung, Yen-Lin Chen
{"title":"User Trajectory Analysis within Intelligent Social Internet-of-things (SIoT)","authors":"Guang Xing Lye, Wai-Khuen Cheng, T. Tan, C. Hung, Yen-Lin Chen","doi":"10.1109/ISPACS48206.2019.8986239","DOIUrl":"https://doi.org/10.1109/ISPACS48206.2019.8986239","url":null,"abstract":"Despite the advancement of Internet-of-Things (IoT) and social network, one of the main challenges in SIoT domain is intelligent service discovery and composition. This paper presents an SIoT architecture with personalized recommendation in order to deliver better service discovery. Our proposed approach has outperformed other methods during the experiments.","PeriodicalId":6765,"journal":{"name":"2019 International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS)","volume":"7 1","pages":"1-2"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74702664","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}