Pub Date : 2018-05-03DOI: 10.1109/EIT.2018.8500087
N. T. M. Saeed, M. Fathi, K. Kuhnert
By the increase of automation, many questions arise about the future of robots in human life, how a robot can communicate with another robot, how it can communicate with a human, and how it can interact with objects of its surrounding-these are some of the critical questions to be answered. For the robot to be able to answer questions and intelligently interact with its environment, it is essential to have a proper understanding of its surrounding; therefore, information must be represented in a way in which a robot can understand them. Semantic technology provides some tools and techniques for expressing information that is understandable by both human and robots. This work presents a novel approach of using Resource Description Framework, RDF, which is a semantic web tool for representing information semantically in the robotics field. For this purpose, a simulated mobile robot equipped with a simulated camera sensor is located in a simulated outdoor environment for navigation. The output of the simulated sensor is collected and converted into a set of statements in RDF format; the obtained statements provide meaning to the detected objects in a way that a robot can understand and utilize.
{"title":"An Approach for Instant Conversion of Sensory Data of a Simulated Sensor of a Mobile Robot into Semantic Information","authors":"N. T. M. Saeed, M. Fathi, K. Kuhnert","doi":"10.1109/EIT.2018.8500087","DOIUrl":"https://doi.org/10.1109/EIT.2018.8500087","url":null,"abstract":"By the increase of automation, many questions arise about the future of robots in human life, how a robot can communicate with another robot, how it can communicate with a human, and how it can interact with objects of its surrounding-these are some of the critical questions to be answered. For the robot to be able to answer questions and intelligently interact with its environment, it is essential to have a proper understanding of its surrounding; therefore, information must be represented in a way in which a robot can understand them. Semantic technology provides some tools and techniques for expressing information that is understandable by both human and robots. This work presents a novel approach of using Resource Description Framework, RDF, which is a semantic web tool for representing information semantically in the robotics field. For this purpose, a simulated mobile robot equipped with a simulated camera sensor is located in a simulated outdoor environment for navigation. The output of the simulated sensor is collected and converted into a set of statements in RDF format; the obtained statements provide meaning to the detected objects in a way that a robot can understand and utilize.","PeriodicalId":188414,"journal":{"name":"2018 IEEE International Conference on Electro/Information Technology (EIT)","volume":"67 5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123030289","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 : 2018-05-03DOI: 10.1109/EIT.2018.8500191
M. Jawad, M. B. Qureshi, Ahsan Nadeem, S. M. Ali, Noman Shabbir, M. N. Rafiq
Conventionally, the power systems are operating separately as AC or DC grids. Both systems have their advantages and disadvantages; however, if the AC loads need to be connected with the DC grid or DC loads with the AC grid, then DC-AC and AC-DC converters are required that results in conversion losses and an increase in the overall cost. Therefore, a comprehensive solution is the hybrid AC-DC grid in which DC loads relate to the DC grid and AC loads relate to the AC grid and one bi-directional converter joins both AC and DC grids and provides need-based power sharing between them. In future, it will be beneficial to operate big organizations, such as data centers, industry, and telecom exchanges under hybrid AC-DC grids because of the ever-increasing DC load demand and to avoid multiple AC-DC-AC conversion losses. Moreover, in recent times the use of Electric Vehicles (EVs) is increasing rapidly and now workplaces are required to have their own EV fast charging docking stations that adds an extra DC load demand for the organizations. Therefore, by keeping the facts in view, we proposed a hybrid AC-DC nano-grid based distributed power generation and power consumption is proposed as a suitable solution to reduce multiple conversion losses within the organizations. The AC and DC load of the Lahore's central telecom exchange is modeled for the simulations. For hybrid AC-DC nano-grid, a droop controller based bi-directional converter is designed for need-based power sharing between AC and DC nano-grids. The proposed hybrid AC-DC nano grid eliminates the excessive voltage conversion problem of telecom exchanges; provide fuel cell and battery bank-based emergency backup solution along with DC fast charging system for the EVs.
{"title":"Bi-Directional Nano Grid Design for Organizations with Plug-In Electric Vehicle Charging at Workplace","authors":"M. Jawad, M. B. Qureshi, Ahsan Nadeem, S. M. Ali, Noman Shabbir, M. N. Rafiq","doi":"10.1109/EIT.2018.8500191","DOIUrl":"https://doi.org/10.1109/EIT.2018.8500191","url":null,"abstract":"Conventionally, the power systems are operating separately as AC or DC grids. Both systems have their advantages and disadvantages; however, if the AC loads need to be connected with the DC grid or DC loads with the AC grid, then DC-AC and AC-DC converters are required that results in conversion losses and an increase in the overall cost. Therefore, a comprehensive solution is the hybrid AC-DC grid in which DC loads relate to the DC grid and AC loads relate to the AC grid and one bi-directional converter joins both AC and DC grids and provides need-based power sharing between them. In future, it will be beneficial to operate big organizations, such as data centers, industry, and telecom exchanges under hybrid AC-DC grids because of the ever-increasing DC load demand and to avoid multiple AC-DC-AC conversion losses. Moreover, in recent times the use of Electric Vehicles (EVs) is increasing rapidly and now workplaces are required to have their own EV fast charging docking stations that adds an extra DC load demand for the organizations. Therefore, by keeping the facts in view, we proposed a hybrid AC-DC nano-grid based distributed power generation and power consumption is proposed as a suitable solution to reduce multiple conversion losses within the organizations. The AC and DC load of the Lahore's central telecom exchange is modeled for the simulations. For hybrid AC-DC nano-grid, a droop controller based bi-directional converter is designed for need-based power sharing between AC and DC nano-grids. The proposed hybrid AC-DC nano grid eliminates the excessive voltage conversion problem of telecom exchanges; provide fuel cell and battery bank-based emergency backup solution along with DC fast charging system for the EVs.","PeriodicalId":188414,"journal":{"name":"2018 IEEE International Conference on Electro/Information Technology (EIT)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123347069","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 : 2018-05-03DOI: 10.1109/EIT.2018.8500105
Balsam Alkouz, Z. Aghbari
The increased popularity of micro-blogging applications (e.g. Twitter) have resulted in the creation of large streams data. Such data provides a great opportunity for researchers to explore event detection. In particular, road traffic detection is of great importance to various applications, i.e. Intelligent Transportation Systems. Recognizing locations in the text of tweets plays an essential role in traffic detection. In this paper, we propose a novel method to identify locations in tweets using cross-lingual (English and Arabic) data collected from Twitter. The collected data (tweets) will be filtered to give emphasis to the United Arab Emirates, UAE, region. Then, features are extracted from the data to classify the tweets into traffic-reporting and non-reporting. The classified tweets are geoparsed and geocoded to acquire the location of reported traffic.
{"title":"Leveraging Cross-Lingual Tweets in Location Recognition","authors":"Balsam Alkouz, Z. Aghbari","doi":"10.1109/EIT.2018.8500105","DOIUrl":"https://doi.org/10.1109/EIT.2018.8500105","url":null,"abstract":"The increased popularity of micro-blogging applications (e.g. Twitter) have resulted in the creation of large streams data. Such data provides a great opportunity for researchers to explore event detection. In particular, road traffic detection is of great importance to various applications, i.e. Intelligent Transportation Systems. Recognizing locations in the text of tweets plays an essential role in traffic detection. In this paper, we propose a novel method to identify locations in tweets using cross-lingual (English and Arabic) data collected from Twitter. The collected data (tweets) will be filtered to give emphasis to the United Arab Emirates, UAE, region. Then, features are extracted from the data to classify the tweets into traffic-reporting and non-reporting. The classified tweets are geoparsed and geocoded to acquire the location of reported traffic.","PeriodicalId":188414,"journal":{"name":"2018 IEEE International Conference on Electro/Information Technology (EIT)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114180561","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 : 2018-05-03DOI: 10.1109/EIT.2018.8500295
Priyanka Sharma, D. Möller
The Automotive Industry is on the verge of digital transformation. The race building fully connected and autonomous cars has begun and it will redefine the way we have been using transportation systems. The goal of connected cars is to provide personalized and safe driving, but connectivity is opening the doors for cyber-attacks. Control Area Network (CAN)-bus is a serial car bus network that connects Electronic Control Units (ECUs), sensors and actuators in a system or subsystem for control applications. Thousands of signals are recorded on the CAN-Bus which can give almost real-time information about the car, driver and the surroundings. This paper proposes a conceptual approach for intrusion detection and prevention systems (IDPSs) for connected cars and an overview of machine learning algorithms for anomaly detection as part of intrusion detection.
{"title":"Protecting ECUs and Vehicles Internal Networks","authors":"Priyanka Sharma, D. Möller","doi":"10.1109/EIT.2018.8500295","DOIUrl":"https://doi.org/10.1109/EIT.2018.8500295","url":null,"abstract":"The Automotive Industry is on the verge of digital transformation. The race building fully connected and autonomous cars has begun and it will redefine the way we have been using transportation systems. The goal of connected cars is to provide personalized and safe driving, but connectivity is opening the doors for cyber-attacks. Control Area Network (CAN)-bus is a serial car bus network that connects Electronic Control Units (ECUs), sensors and actuators in a system or subsystem for control applications. Thousands of signals are recorded on the CAN-Bus which can give almost real-time information about the car, driver and the surroundings. This paper proposes a conceptual approach for intrusion detection and prevention systems (IDPSs) for connected cars and an overview of machine learning algorithms for anomaly detection as part of intrusion detection.","PeriodicalId":188414,"journal":{"name":"2018 IEEE International Conference on Electro/Information Technology (EIT)","volume":"243 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121875176","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 : 2018-05-03DOI: 10.1109/EIT.2018.8500179
Won-Jae Yi, Boyang Wang, Bruno Fernandes dos Santos, Eduardo Fonseca Carvalho, J. Saniie
In the remote health monitoring system, it is crucial to identify and analyze the current users' status accurately. The accuracy depends on many different aspects including physical conditions, surrounding environmental conditions, users' distinct features and other factors. In this paper, we investigate the enhacement possibility of IoT based health monitoring system by applying neural network. By training the collected user data from different types of medical emergency-related scenarios, the system would gain better accuracy over the traditional thresholding data analysis systems. In this study, we focus on applying neural network to the fall detection application which involves wireless wearable sensors with accelerometers and a gyroscope. We utilize multilayer perceptron neural network to train user movement datasets including positive falls (falling events) and negative falls (non-falling events). This system design approach has the potential to be extended to multi-purpose user activity and health monitoring system, including people who have potential in needs of medical attentions and daily activity tracking.
{"title":"Design Flow of Neural Network Application for IoT Based Fall Detection System","authors":"Won-Jae Yi, Boyang Wang, Bruno Fernandes dos Santos, Eduardo Fonseca Carvalho, J. Saniie","doi":"10.1109/EIT.2018.8500179","DOIUrl":"https://doi.org/10.1109/EIT.2018.8500179","url":null,"abstract":"In the remote health monitoring system, it is crucial to identify and analyze the current users' status accurately. The accuracy depends on many different aspects including physical conditions, surrounding environmental conditions, users' distinct features and other factors. In this paper, we investigate the enhacement possibility of IoT based health monitoring system by applying neural network. By training the collected user data from different types of medical emergency-related scenarios, the system would gain better accuracy over the traditional thresholding data analysis systems. In this study, we focus on applying neural network to the fall detection application which involves wireless wearable sensors with accelerometers and a gyroscope. We utilize multilayer perceptron neural network to train user movement datasets including positive falls (falling events) and negative falls (non-falling events). This system design approach has the potential to be extended to multi-purpose user activity and health monitoring system, including people who have potential in needs of medical attentions and daily activity tracking.","PeriodicalId":188414,"journal":{"name":"2018 IEEE International Conference on Electro/Information Technology (EIT)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123806013","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 : 2018-05-03DOI: 10.1109/EIT.2018.8500213
Hayder O. Alwan, Hamidreza Sadeghian, Zhifang Wang
In smart grid, the demand side management techniques need to be designed to process a large number of controllable loads of several types, this results in increased sustainability of the grid, as well as reduced the operational cost. In this paper, we proposed a framework to study decentralized demand side management in a distributed network which contains a variety of loads of two demand types; residential load and commercial load. Specifically, each of residential load and commercial load has local renewable generation such as rooftop PV and flexible appliances and by making an optimum individual scheduling will reduce the electricity bill with a manageable sacrifice of customers convenience and comfort according time-of-using (TOU) prices. In our simulation model commercial load bus on bus seventeenth, with twenty-nine households employed to demonstrate the performance of the proposed DSM for large number of appliances. Using the developed simulation model we examine the performance of decentralized DSM and study their impact on the distribution network operation and renewable generation, overall voltage deviation, real power loss, and possible problems such as reverse power flows, voltage rise have examined and compared.
{"title":"Decentralized Demand Side Management Optimization for Residential and Commercial Load","authors":"Hayder O. Alwan, Hamidreza Sadeghian, Zhifang Wang","doi":"10.1109/EIT.2018.8500213","DOIUrl":"https://doi.org/10.1109/EIT.2018.8500213","url":null,"abstract":"In smart grid, the demand side management techniques need to be designed to process a large number of controllable loads of several types, this results in increased sustainability of the grid, as well as reduced the operational cost. In this paper, we proposed a framework to study decentralized demand side management in a distributed network which contains a variety of loads of two demand types; residential load and commercial load. Specifically, each of residential load and commercial load has local renewable generation such as rooftop PV and flexible appliances and by making an optimum individual scheduling will reduce the electricity bill with a manageable sacrifice of customers convenience and comfort according time-of-using (TOU) prices. In our simulation model commercial load bus on bus seventeenth, with twenty-nine households employed to demonstrate the performance of the proposed DSM for large number of appliances. Using the developed simulation model we examine the performance of decentralized DSM and study their impact on the distribution network operation and renewable generation, overall voltage deviation, real power loss, and possible problems such as reverse power flows, voltage rise have examined and compared.","PeriodicalId":188414,"journal":{"name":"2018 IEEE International Conference on Electro/Information Technology (EIT)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115111490","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 : 2018-05-03DOI: 10.1109/EIT.2018.8500107
H. Alhichri, N. Alajlan, Y. Bazi, T. Rabczuk
In recent years the problem of scene classification in remote sensing has attracted a considerable amount of attention. Solution for this important problem based on deep convolutional neural networks (CNN) are currently state-of-the-art. So far all CNNs used images of fixed size (typically $224times 224$ which commonly used in other fields of computer vision). In this paper, we propose a multi-scale deep CNN architecture that can accept variable image sizes. We achieve this by using multiple CNN, that share some or all parameters, followed by a merge layer, fully connected layers, and finally a softmax layer for classification. In each epoch we train the network with a batch of images of all scales. We have implemented this architecture using three SqueezeNet CNNs trained on three different scales of scene images. Then we carried out experiments on three well know datasets, namely UC Merced, KSA, and AID datasets. Preliminary results show that this multi-scale CNN do converge just as the traditional single-scale training, and leads to better testing accuracy.
{"title":"Multi-Scale Convolutional Neural Network for Remote Sensing Scene Classification","authors":"H. Alhichri, N. Alajlan, Y. Bazi, T. Rabczuk","doi":"10.1109/EIT.2018.8500107","DOIUrl":"https://doi.org/10.1109/EIT.2018.8500107","url":null,"abstract":"In recent years the problem of scene classification in remote sensing has attracted a considerable amount of attention. Solution for this important problem based on deep convolutional neural networks (CNN) are currently state-of-the-art. So far all CNNs used images of fixed size (typically $224times 224$ which commonly used in other fields of computer vision). In this paper, we propose a multi-scale deep CNN architecture that can accept variable image sizes. We achieve this by using multiple CNN, that share some or all parameters, followed by a merge layer, fully connected layers, and finally a softmax layer for classification. In each epoch we train the network with a batch of images of all scales. We have implemented this architecture using three SqueezeNet CNNs trained on three different scales of scene images. Then we carried out experiments on three well know datasets, namely UC Merced, KSA, and AID datasets. Preliminary results show that this multi-scale CNN do converge just as the traditional single-scale training, and leads to better testing accuracy.","PeriodicalId":188414,"journal":{"name":"2018 IEEE International Conference on Electro/Information Technology (EIT)","volume":"187 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127061281","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 : 2018-05-03DOI: 10.1109/EIT.2018.8500104
Y. Almalaq, A. Alateeq, M. Matin
This paper introduces a transformerless high gain switched-inductor switched-capacitor Cuk converter in step-up mode. This kind of converter provides a negative to positive step-up DC-DC voltage conversion. The main advantages of using the proposed converter over the classical Cuk converter are achieving high voltage gain with low voltage stress on semiconductor devices and using fewer components compared with other Cuk converters reached the same level of high voltage gain. The proposed converter has the ability to reach 13 times the input voltage when $mathbf{D}=0.75$ where D is the duty cycle. This high voltage gain is achieved by using a switched-inductor and switched-capacitor techniques. A detailed theoretical analysis of the continuous conduction mode (CCM) is represented. Likewise, the major aspects of circuit design have been derived. The presented paper shows a comparison between the proposed Cuk converter with other Cuk converter topologies. The proposed converter has been designed for 12V input voltage, −152V output voltage, 100W rated power, 50kHz switching frequency, and 75% duty cycle. A circuit has been developed in MATLAB/SIMULINK and results are discussed.
{"title":"A Transformerless High Gain Switched-Inductor Switched-Capacitor Cuk Converter in Step-Up Mode","authors":"Y. Almalaq, A. Alateeq, M. Matin","doi":"10.1109/EIT.2018.8500104","DOIUrl":"https://doi.org/10.1109/EIT.2018.8500104","url":null,"abstract":"This paper introduces a transformerless high gain switched-inductor switched-capacitor Cuk converter in step-up mode. This kind of converter provides a negative to positive step-up DC-DC voltage conversion. The main advantages of using the proposed converter over the classical Cuk converter are achieving high voltage gain with low voltage stress on semiconductor devices and using fewer components compared with other Cuk converters reached the same level of high voltage gain. The proposed converter has the ability to reach 13 times the input voltage when $mathbf{D}=0.75$ where D is the duty cycle. This high voltage gain is achieved by using a switched-inductor and switched-capacitor techniques. A detailed theoretical analysis of the continuous conduction mode (CCM) is represented. Likewise, the major aspects of circuit design have been derived. The presented paper shows a comparison between the proposed Cuk converter with other Cuk converter topologies. The proposed converter has been designed for 12V input voltage, −152V output voltage, 100W rated power, 50kHz switching frequency, and 75% duty cycle. A circuit has been developed in MATLAB/SIMULINK and results are discussed.","PeriodicalId":188414,"journal":{"name":"2018 IEEE International Conference on Electro/Information Technology (EIT)","volume":"78 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123151501","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 : 2018-05-03DOI: 10.1109/EIT.2018.8500176
Jing Wu, Andres Jacoby, D. Llamocca, B. Sangeorzan
This work presents a custom hardware architecture for crank-angle-resolved engine cylinder pressure estimation that can accept inputs such as speed, manifold pressure and throttle position, and deliver cylinder pressure in real-time, at engine speeds covering the useful operating range of most engines (up to 10,000 rpm). The hardware, placed in a reconfigurable embedded system for real-time validation, was tested using results of a model derived from actual engine data (13 sets). The hardware, implemented in 32-bit Dual Fixed-Point arithmetic, exhibits results that are very close to those of a 64-bit floating-point software model. This work attempts to show Dual Fixed-Point as a good alternative for high precision operations in automotive applications, where floating point is believed to be the only option.
{"title":"An Architecture for Real-Time Estimation of Crank-Angle-Resolved Engine Cylinder Pressure","authors":"Jing Wu, Andres Jacoby, D. Llamocca, B. Sangeorzan","doi":"10.1109/EIT.2018.8500176","DOIUrl":"https://doi.org/10.1109/EIT.2018.8500176","url":null,"abstract":"This work presents a custom hardware architecture for crank-angle-resolved engine cylinder pressure estimation that can accept inputs such as speed, manifold pressure and throttle position, and deliver cylinder pressure in real-time, at engine speeds covering the useful operating range of most engines (up to 10,000 rpm). The hardware, placed in a reconfigurable embedded system for real-time validation, was tested using results of a model derived from actual engine data (13 sets). The hardware, implemented in 32-bit Dual Fixed-Point arithmetic, exhibits results that are very close to those of a 64-bit floating-point software model. This work attempts to show Dual Fixed-Point as a good alternative for high precision operations in automotive applications, where floating point is believed to be the only option.","PeriodicalId":188414,"journal":{"name":"2018 IEEE International Conference on Electro/Information Technology (EIT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131270054","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 : 2018-05-03DOI: 10.1109/EIT.2018.8500305
Md Sabbir Zaman, B. Morshed
Wireless resistive analog passive (WRAP) sensors are low cost, battery less, body-worn physiological sensors. Portable Scanner is a hardware device capable of acquiring physiological signals from multiple types of WRAP sensors using amplitude modulation (AM) technique. The signal acquisition relies on inductive loading principal of signal due to impedance mismatch between the LC resonator circuits of scanner and the wireless passive sensor. The physiological signals of the subject affect the impedance that results in the mismatch, which eventually modulates the amplitude of scanner-generated carrier wave at 6.15 MHz. The DDS along with RF power amplifier of the scanner generates the carrier wave. The AM wave's top envelope is picked up by an envelope demodulator $(mathbf{f} >> 1 mathbf{KHz})$ from the AM signal. The signal is processed in analog domain by utilizing a 2nd order Butterworth low pass filter (1.5 KHz), a variable gain (Av) amplifier $(mathbf{Av}_{mathbf{min}}=1, mathbf{Av}_{mathbf{max}}=9)$, then signal is acquired in digital domain via 12 bit ADC and finally is transmitted to a smartphone application via a Class 2 Bluetooth wireless link at a baud rate of 115.2 kbps. The developed scanner device uses a 4-layer PCB $(14 mathbf{cm} times 5 mathbf{cm}times 1.25 mathbf{cm})$, and contained a 32-bit low power flash microcontroller (STM32L476) based on ARM Cortex - M processor. The device is powered by a 2000 mAh Li-Poly battery. The circuit consumes 0.69 mA during scanning burst, which can sustain continuous scanning of more than 2028 hours (for consumption rate of 0.7).
{"title":"Design and Verification of a Portable Scanner for Body-Worn Wireless Resistive Analog Passive (WRAP) Sensors","authors":"Md Sabbir Zaman, B. Morshed","doi":"10.1109/EIT.2018.8500305","DOIUrl":"https://doi.org/10.1109/EIT.2018.8500305","url":null,"abstract":"Wireless resistive analog passive (WRAP) sensors are low cost, battery less, body-worn physiological sensors. Portable Scanner is a hardware device capable of acquiring physiological signals from multiple types of WRAP sensors using amplitude modulation (AM) technique. The signal acquisition relies on inductive loading principal of signal due to impedance mismatch between the LC resonator circuits of scanner and the wireless passive sensor. The physiological signals of the subject affect the impedance that results in the mismatch, which eventually modulates the amplitude of scanner-generated carrier wave at 6.15 MHz. The DDS along with RF power amplifier of the scanner generates the carrier wave. The AM wave's top envelope is picked up by an envelope demodulator $(mathbf{f} >> 1 mathbf{KHz})$ from the AM signal. The signal is processed in analog domain by utilizing a 2nd order Butterworth low pass filter (1.5 KHz), a variable gain (Av) amplifier $(mathbf{Av}_{mathbf{min}}=1, mathbf{Av}_{mathbf{max}}=9)$, then signal is acquired in digital domain via 12 bit ADC and finally is transmitted to a smartphone application via a Class 2 Bluetooth wireless link at a baud rate of 115.2 kbps. The developed scanner device uses a 4-layer PCB $(14 mathbf{cm} times 5 mathbf{cm}times 1.25 mathbf{cm})$, and contained a 32-bit low power flash microcontroller (STM32L476) based on ARM Cortex - M processor. The device is powered by a 2000 mAh Li-Poly battery. The circuit consumes 0.69 mA during scanning burst, which can sustain continuous scanning of more than 2028 hours (for consumption rate of 0.7).","PeriodicalId":188414,"journal":{"name":"2018 IEEE International Conference on Electro/Information Technology (EIT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130760948","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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