Pub Date : 2020-06-01DOI: 10.1109/ISSC49989.2020.9180190
Mariusz P. Wilk, M. Walsh, B. O’flynn
Human motion tracking systems are widely used in various application spaces, such as motion capture, rehabilitation, or sports. There exists a number of such systems in the State-Of-The-Art (SOA) that vary in price, complexity, accuracy and the target applications. With the continued advances in system integration and miniaturization, wearable motion trackers gain in popularity in the research community. The opto-inertial trackers with multimodal sensor fusion algorithms are some of the common approaches found in SOA. However, these trackers tend to be expensive and have high computational requirements. In this work, we present a prototype version of our opto-inertial, motion tracking system that offers a low-cost alternative. The 3D position and orientation are determined by fusing optical and inertial sensor data together with knowledge about two external reference points using a purpose-designed data fusion algorithm. An experimental validation was carried out on one of the use cases that this system is intended for, i.e. barbell squat in strength training. The results showed that the total RMSE in position and orientation was 32.8 mm and 0.89 degree, respectively. It operated in real-time at 20 frames per second.
{"title":"Low Cost Embedded Multimodal Opto-Inertial Human Motion Tracking System","authors":"Mariusz P. Wilk, M. Walsh, B. O’flynn","doi":"10.1109/ISSC49989.2020.9180190","DOIUrl":"https://doi.org/10.1109/ISSC49989.2020.9180190","url":null,"abstract":"Human motion tracking systems are widely used in various application spaces, such as motion capture, rehabilitation, or sports. There exists a number of such systems in the State-Of-The-Art (SOA) that vary in price, complexity, accuracy and the target applications. With the continued advances in system integration and miniaturization, wearable motion trackers gain in popularity in the research community. The opto-inertial trackers with multimodal sensor fusion algorithms are some of the common approaches found in SOA. However, these trackers tend to be expensive and have high computational requirements. In this work, we present a prototype version of our opto-inertial, motion tracking system that offers a low-cost alternative. The 3D position and orientation are determined by fusing optical and inertial sensor data together with knowledge about two external reference points using a purpose-designed data fusion algorithm. An experimental validation was carried out on one of the use cases that this system is intended for, i.e. barbell squat in strength training. The results showed that the total RMSE in position and orientation was 32.8 mm and 0.89 degree, respectively. It operated in real-time at 20 frames per second.","PeriodicalId":351013,"journal":{"name":"2020 31st Irish Signals and Systems Conference (ISSC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129559912","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-06-01DOI: 10.1109/ISSC49989.2020.9180215
J. Blackledge, N. Mosola
This paper considers an algorithm for transferring a digital image over an open network using a No-key(s) Protocol or Three-Way Pass and phase-only encryption/decryption. After providing a short study on the theoretical background to the method, an algorithm is presented on a step-by-step basis. Cryptanalysis is undertaken for the three intercept and single intercept cases, when it is assumed that the encrypted data is intercepted in its entirety for each pass or for any single pass, respectively. The algorithm focuses on the exchange of a JPEG image although in principle, the approach is independent of the format of the image file that is used. Prototype MATLAB functions are provided for the validation of the approach and for further development by interested readers.
{"title":"Digital Image Exchange using a No-key(s) Protocol with Phase-only Encryption","authors":"J. Blackledge, N. Mosola","doi":"10.1109/ISSC49989.2020.9180215","DOIUrl":"https://doi.org/10.1109/ISSC49989.2020.9180215","url":null,"abstract":"This paper considers an algorithm for transferring a digital image over an open network using a No-key(s) Protocol or Three-Way Pass and phase-only encryption/decryption. After providing a short study on the theoretical background to the method, an algorithm is presented on a step-by-step basis. Cryptanalysis is undertaken for the three intercept and single intercept cases, when it is assumed that the encrypted data is intercepted in its entirety for each pass or for any single pass, respectively. The algorithm focuses on the exchange of a JPEG image although in principle, the approach is independent of the format of the image file that is used. Prototype MATLAB functions are provided for the validation of the approach and for further development by interested readers.","PeriodicalId":351013,"journal":{"name":"2020 31st Irish Signals and Systems Conference (ISSC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129912950","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-06-01DOI: 10.1109/ISSC49989.2020.9180202
Xutong Wu, T. Siriburanon, R. Staszewski
This paper proposes a time-domain multiply-accumulator (MAC) circuit exploiting the use of a digital-to-time multiplier (DTM) unit for performing convolutional operations and designed in 28nm CMOS. As the foundational calculation of state-of-the-art convolutional neural network (CNN) models, convolutional operation could normally be executed millions of times in one CNN task. The proposed circuit is designed to support this large computational resource requirement during the CNN computations. It is running in time-domain with 6-bit resolution (1 sign bit) and performs calculations based on corresponding time delays. Compared with other analog-domain propositions, time-domain designs perform better, with higher operating frequencies up to 50 MHz. In schematic simulations, the proposed DTM unit, operating with 5 bits, achieves 0.1 GOPS ideal throughput and consumes 74.79 µW at 1.0V supply.
{"title":"Time-Domain Multiply-Accumulator using Digital-to-Time Multiplier for CNN Processors in 28-nm CMOS","authors":"Xutong Wu, T. Siriburanon, R. Staszewski","doi":"10.1109/ISSC49989.2020.9180202","DOIUrl":"https://doi.org/10.1109/ISSC49989.2020.9180202","url":null,"abstract":"This paper proposes a time-domain multiply-accumulator (MAC) circuit exploiting the use of a digital-to-time multiplier (DTM) unit for performing convolutional operations and designed in 28nm CMOS. As the foundational calculation of state-of-the-art convolutional neural network (CNN) models, convolutional operation could normally be executed millions of times in one CNN task. The proposed circuit is designed to support this large computational resource requirement during the CNN computations. It is running in time-domain with 6-bit resolution (1 sign bit) and performs calculations based on corresponding time delays. Compared with other analog-domain propositions, time-domain designs perform better, with higher operating frequencies up to 50 MHz. In schematic simulations, the proposed DTM unit, operating with 5 bits, achieves 0.1 GOPS ideal throughput and consumes 74.79 µW at 1.0V supply.","PeriodicalId":351013,"journal":{"name":"2020 31st Irish Signals and Systems Conference (ISSC)","volume":"256 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132033076","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-06-01DOI: 10.1109/ISSC49989.2020.9180159
Keith Phelan, D. Riordan
Ringforts are one of the most populous field monuments in Ireland with approximately 45000 examples surviving to date. Their distribution and dispersal patterns are key to our understanding of the habitation patterns of our ancestors. Due to the nature of these structures and the construction materials used, centuries of abandonment means that they often go unnoticed at ground level, while being easily identified from an aerial perspective. The increased requirements of land use for the development of urban areas, infrastructure and increased industrialised farming practices means that these monuments are under threat. Recent developments in the field of machine learning coupled with access to hi-resolution multi-spectral satellite imagery from Open Data sources, presents the opportunity to investigate the development of a system for the automated detection of these features. If successful, such a system could provide an automated, efficient and cost effective tool for the detection of interference or destruction of known sites as well as the discovery of new ones.
{"title":"Detection of ringforts from aerial photography using machine learning","authors":"Keith Phelan, D. Riordan","doi":"10.1109/ISSC49989.2020.9180159","DOIUrl":"https://doi.org/10.1109/ISSC49989.2020.9180159","url":null,"abstract":"Ringforts are one of the most populous field monuments in Ireland with approximately 45000 examples surviving to date. Their distribution and dispersal patterns are key to our understanding of the habitation patterns of our ancestors. Due to the nature of these structures and the construction materials used, centuries of abandonment means that they often go unnoticed at ground level, while being easily identified from an aerial perspective. The increased requirements of land use for the development of urban areas, infrastructure and increased industrialised farming practices means that these monuments are under threat. Recent developments in the field of machine learning coupled with access to hi-resolution multi-spectral satellite imagery from Open Data sources, presents the opportunity to investigate the development of a system for the automated detection of these features. If successful, such a system could provide an automated, efficient and cost effective tool for the detection of interference or destruction of known sites as well as the discovery of new ones.","PeriodicalId":351013,"journal":{"name":"2020 31st Irish Signals and Systems Conference (ISSC)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130998442","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-06-01DOI: 10.1109/ISSC49989.2020.9180176
Cathal Ferry, J. Connolly
Energy saving and energy conservation are fast becoming key ideologies in the construction and creation of modern data centres and IT infrastructure. This applies to large scale deployments and on smaller to more intermediate scale sites. Data centres consume large quantities of energy and contribute to carbon dioxide (CO2) emissions. Reducing CO2output using methods such as sustainable power generation and better energy efficiency can help mitigate against the effects of global warming. This paper proposes methods of saving energy in IT equipment by monitoring key power statistics such as power factor to determine the efficiency of the power being used by network equipment. This is achieved using an open-source power factor meter which is not only low cost but also accurate. The meter measures power factor as well as true power, apparent power, reactive power, mains voltage, current, and mains frequency to determine the energy efficiency of the installation or equipment. Readings are measured using three primary sensors; a current transformer, voltage transformer, and a mains frequency sensor. The system is designed for use with single-phase systems and incorporates a local HMI and a cloud-based CMS system. All of the software and hardware elements used are open source and therefore low cost.
{"title":"Open Source Power Quality Meter with cloud monitoring","authors":"Cathal Ferry, J. Connolly","doi":"10.1109/ISSC49989.2020.9180176","DOIUrl":"https://doi.org/10.1109/ISSC49989.2020.9180176","url":null,"abstract":"Energy saving and energy conservation are fast becoming key ideologies in the construction and creation of modern data centres and IT infrastructure. This applies to large scale deployments and on smaller to more intermediate scale sites. Data centres consume large quantities of energy and contribute to carbon dioxide (CO2) emissions. Reducing CO2output using methods such as sustainable power generation and better energy efficiency can help mitigate against the effects of global warming. This paper proposes methods of saving energy in IT equipment by monitoring key power statistics such as power factor to determine the efficiency of the power being used by network equipment. This is achieved using an open-source power factor meter which is not only low cost but also accurate. The meter measures power factor as well as true power, apparent power, reactive power, mains voltage, current, and mains frequency to determine the energy efficiency of the installation or equipment. Readings are measured using three primary sensors; a current transformer, voltage transformer, and a mains frequency sensor. The system is designed for use with single-phase systems and incorporates a local HMI and a cloud-based CMS system. All of the software and hardware elements used are open source and therefore low cost.","PeriodicalId":351013,"journal":{"name":"2020 31st Irish Signals and Systems Conference (ISSC)","volume":"295 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132800909","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-06-01DOI: 10.1109/ISSC49989.2020.9180207
Davide Villa, Chih-kuang Lin, Adam Kuenzi, Michael Lang
Wireless networks are ubiquitous in our modern world, and we rely more and more on their continuous and reliable operation for battery-powered devices. Networks that self-maintain and self-heal are inherently more reliable. We study efficient and effective network self-healing and update methods for routing recovery following routing failures in a wireless multi-hop network. Network update processes are important since they enable local nodes to maintain the latest and updated neighbor information for routing given the network changes caused by failures. Network update also introduces control signals overhead. In this paper, we investigate the trade-off between routing performance and overhead cost with different network update algorithms and we characterize the performance of the proposed algorithms using network simulations. We show that network updates have positive impacts on routing. In particular, the on-demand route update method provides better results among compared techniques. The improvement is varying depending on the network topology and failure condition scenario.
{"title":"On-demand updates after a node failure in a wireless network","authors":"Davide Villa, Chih-kuang Lin, Adam Kuenzi, Michael Lang","doi":"10.1109/ISSC49989.2020.9180207","DOIUrl":"https://doi.org/10.1109/ISSC49989.2020.9180207","url":null,"abstract":"Wireless networks are ubiquitous in our modern world, and we rely more and more on their continuous and reliable operation for battery-powered devices. Networks that self-maintain and self-heal are inherently more reliable. We study efficient and effective network self-healing and update methods for routing recovery following routing failures in a wireless multi-hop network. Network update processes are important since they enable local nodes to maintain the latest and updated neighbor information for routing given the network changes caused by failures. Network update also introduces control signals overhead. In this paper, we investigate the trade-off between routing performance and overhead cost with different network update algorithms and we characterize the performance of the proposed algorithms using network simulations. We show that network updates have positive impacts on routing. In particular, the on-demand route update method provides better results among compared techniques. The improvement is varying depending on the network topology and failure condition scenario.","PeriodicalId":351013,"journal":{"name":"2020 31st Irish Signals and Systems Conference (ISSC)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115727001","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-06-01DOI: 10.1109/ISSC49989.2020.9180209
George D. O’Mahony, Philip J. Harris, Colin C. Murphy
Knowledge of the wireless channel is pivotal for wireless communication links but varies for multiple reasons. The radio spectrum changes due to the number of connected devices, demand, packet size or services in operation, while fading levels, obstacles, path losses, and spurious (non-)malicious interference fluctuate in the physical environment. Typically, these channels are applicable to the time series class of data science problems, as the primary data points are measured over a period. In the case of wireless sensor networks, which regularly provide the device to access point communication links in Internet of Things applications, determining the wireless channel in operation permits channel access. Generally, a clear channel assessment is performed to determine whether a wireless transmission can be executed, which is an approach containing limitations. In this study, received in-phase (I) and quadrature-phase (Q) samples are collected from the wireless channel using a software-defined radio (SDR) based procedure and directly analyzed using python and Matlab. Features are extracted from the probability density function and statistical analysis of the received I/Q samples and used as the training data for the two chosen machine learning methods. Data is collected and produced over wires, to avoid interfering with other networks, using SDRs and Raspberry Pi embedded devices, which utilize available open-source libraries. Data is examined for the signal-free (noise), legitimate signal (ZigBee) and jamming signal (continuous wave) cases in a live laboratory environment. Support vector machine and Random Forest models are each designed and compared as channel identifiers for these signal types.
{"title":"Investigating Supervised Machine Learning Techniques for Channel Identification in Wireless Sensor Networks","authors":"George D. O’Mahony, Philip J. Harris, Colin C. Murphy","doi":"10.1109/ISSC49989.2020.9180209","DOIUrl":"https://doi.org/10.1109/ISSC49989.2020.9180209","url":null,"abstract":"Knowledge of the wireless channel is pivotal for wireless communication links but varies for multiple reasons. The radio spectrum changes due to the number of connected devices, demand, packet size or services in operation, while fading levels, obstacles, path losses, and spurious (non-)malicious interference fluctuate in the physical environment. Typically, these channels are applicable to the time series class of data science problems, as the primary data points are measured over a period. In the case of wireless sensor networks, which regularly provide the device to access point communication links in Internet of Things applications, determining the wireless channel in operation permits channel access. Generally, a clear channel assessment is performed to determine whether a wireless transmission can be executed, which is an approach containing limitations. In this study, received in-phase (I) and quadrature-phase (Q) samples are collected from the wireless channel using a software-defined radio (SDR) based procedure and directly analyzed using python and Matlab. Features are extracted from the probability density function and statistical analysis of the received I/Q samples and used as the training data for the two chosen machine learning methods. Data is collected and produced over wires, to avoid interfering with other networks, using SDRs and Raspberry Pi embedded devices, which utilize available open-source libraries. Data is examined for the signal-free (noise), legitimate signal (ZigBee) and jamming signal (continuous wave) cases in a live laboratory environment. Support vector machine and Random Forest models are each designed and compared as channel identifiers for these signal types.","PeriodicalId":351013,"journal":{"name":"2020 31st Irish Signals and Systems Conference (ISSC)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131565493","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-06-01DOI: 10.1109/ISSC49989.2020.9180198
Kieran Hughes, K. Mclaughlin, S. Sezer
Significant advancements in Intrusion Detection Systems has led to improved alerts. However, Intrusion Response Systems which aim to automatically respond to these alerts, is a research area which is not yet advanced enough to benefit from full automation. In Security Operations Centres, analysts can implement countermeasures using knowledge and past experience to adapt to new attacks. Attempts at automated Intrusion Response Systems fall short when a new attack occurs to which the system has no specific knowledge or effective countermeasure to apply, even leading to overkill countermeasures such as restarting services and blocking ports or IPs. In this paper, a countermeasure standard is proposed which enables countermeasure intelligence sharing, automated countermeasure adoption and execution by an Intrusion Response System. An attack scenario is created on an emulated network using the Common Open Research Emulator, where an insider attack attempts to exploit a buffer overflow on an Exim mail server. Experiments demonstrate that an Intrusion Response System with dynamic countermeasure knowledge can stop attacks that would otherwise succeed with a static predefined countermeasure approach.
入侵检测系统的重大进步导致了警报的改进。然而，旨在自动响应这些警报的入侵响应系统是一个尚不够先进的研究领域，无法从完全自动化中受益。在安全运营中心，分析人员可以利用知识和过去的经验实施对策，以适应新的攻击。当新的攻击发生时，系统没有特定的知识或有效的应对措施，甚至导致重新启动服务和阻止端口或ip等过度的应对措施，自动入侵响应系统的尝试就会失败。本文提出了一种对抗标准，实现了入侵响应系统对对抗情报的共享、对对抗的自动采用和执行。使用Common Open Research Emulator在模拟网络上创建攻击场景，其中内部攻击试图利用Exim邮件服务器上的缓冲区溢出。实验表明，具有动态对抗知识的入侵响应系统能够有效阻止静态预定义对抗方法无法成功实施的攻击。
{"title":"Dynamic Countermeasure Knowledge for Intrusion Response Systems","authors":"Kieran Hughes, K. Mclaughlin, S. Sezer","doi":"10.1109/ISSC49989.2020.9180198","DOIUrl":"https://doi.org/10.1109/ISSC49989.2020.9180198","url":null,"abstract":"Significant advancements in Intrusion Detection Systems has led to improved alerts. However, Intrusion Response Systems which aim to automatically respond to these alerts, is a research area which is not yet advanced enough to benefit from full automation. In Security Operations Centres, analysts can implement countermeasures using knowledge and past experience to adapt to new attacks. Attempts at automated Intrusion Response Systems fall short when a new attack occurs to which the system has no specific knowledge or effective countermeasure to apply, even leading to overkill countermeasures such as restarting services and blocking ports or IPs. In this paper, a countermeasure standard is proposed which enables countermeasure intelligence sharing, automated countermeasure adoption and execution by an Intrusion Response System. An attack scenario is created on an emulated network using the Common Open Research Emulator, where an insider attack attempts to exploit a buffer overflow on an Exim mail server. Experiments demonstrate that an Intrusion Response System with dynamic countermeasure knowledge can stop attacks that would otherwise succeed with a static predefined countermeasure approach.","PeriodicalId":351013,"journal":{"name":"2020 31st Irish Signals and Systems Conference (ISSC)","volume":"68 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132424713","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-06-01DOI: 10.1109/ISSC49989.2020.9180200
P. Corcoran, Hossein Javidnia, Joseph Lemley, Viktor Varkarakis
Recent Advances in Artificial Intelligence (AI), particularly in the field of compute vision, have been driven by the availability of large public datasets. However, as AI begins to move into embedded devices there will be a growing need for tools to acquire and re-acquire datasets from specific sensing systems to train new device models. In this paper, a roadmap in introduced for a data-acquisition framework that can build the large synthetic datasets required to train AI systems from small seed datasets. A key element to justify such a framework is the validation of the generated dataset and example results are shown from preliminary work on biometric (facial) datasets.
{"title":"Generative Augmented Dataset and Annotation Frameworks for Artificial Intelligence (GADAFAI)","authors":"P. Corcoran, Hossein Javidnia, Joseph Lemley, Viktor Varkarakis","doi":"10.1109/ISSC49989.2020.9180200","DOIUrl":"https://doi.org/10.1109/ISSC49989.2020.9180200","url":null,"abstract":"Recent Advances in Artificial Intelligence (AI), particularly in the field of compute vision, have been driven by the availability of large public datasets. However, as AI begins to move into embedded devices there will be a growing need for tools to acquire and re-acquire datasets from specific sensing systems to train new device models. In this paper, a roadmap in introduced for a data-acquisition framework that can build the large synthetic datasets required to train AI systems from small seed datasets. A key element to justify such a framework is the validation of the generated dataset and example results are shown from preliminary work on biometric (facial) datasets.","PeriodicalId":351013,"journal":{"name":"2020 31st Irish Signals and Systems Conference (ISSC)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121566841","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-06-01DOI: 10.1109/ISSC49989.2020.9180172
Con Cronin, A. Conway, Anshul Awasthi, Joseph Walsh
This paper details a proof-of-concept material handling system integrated to a small-scale, self-navigating AIV. The prototype has the ability to autonomously navigate from one manufacturing cell to another. It loads and unloads material from one fixed conveyor to another in an environment that includes confined and populated passageways. This paper advances the concept of the material handling system to communicate directly with the production equipment. A successful development of an material handling system with an AIV in automation proposes to increase productivity in manufacturing while securing jobs in a competitive market. AIVs promote flexibility within the factory floor and increase the realisation of Industry 4.0.
{"title":"Flexible Manufacturing using Automated Material Handling and Autonomous Intelligent Vehicles","authors":"Con Cronin, A. Conway, Anshul Awasthi, Joseph Walsh","doi":"10.1109/ISSC49989.2020.9180172","DOIUrl":"https://doi.org/10.1109/ISSC49989.2020.9180172","url":null,"abstract":"This paper details a proof-of-concept material handling system integrated to a small-scale, self-navigating AIV. The prototype has the ability to autonomously navigate from one manufacturing cell to another. It loads and unloads material from one fixed conveyor to another in an environment that includes confined and populated passageways. This paper advances the concept of the material handling system to communicate directly with the production equipment. A successful development of an material handling system with an AIV in automation proposes to increase productivity in manufacturing while securing jobs in a competitive market. AIVs promote flexibility within the factory floor and increase the realisation of Industry 4.0.","PeriodicalId":351013,"journal":{"name":"2020 31st Irish Signals and Systems Conference (ISSC)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125016523","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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