Pub Date : 2020-05-01DOI: 10.1109/DCOSS49796.2020.00033
M. Kawamoto, T. Hamamoto
This paper presents a method to identify sound sources for structural monitoring, known as building health monitoring. This method allows to evaluate deterioration and damage of buildings by analyzing environmental sounds. The proposed method determines the location and features of sounds generated within a building, with its main characteristics being: (1) planar direction and height estimation; (2) visualization of sound features according to loudness, continuity, and pitch. The capabilities of the proposed building health monitoring method are verified using environmental sound data acquired at a building in Gunkanjima, which is a world heritage site from Japan.
{"title":"Building Health Monitoring Using Computational Auditory Scene Analysis","authors":"M. Kawamoto, T. Hamamoto","doi":"10.1109/DCOSS49796.2020.00033","DOIUrl":"https://doi.org/10.1109/DCOSS49796.2020.00033","url":null,"abstract":"This paper presents a method to identify sound sources for structural monitoring, known as building health monitoring. This method allows to evaluate deterioration and damage of buildings by analyzing environmental sounds. The proposed method determines the location and features of sounds generated within a building, with its main characteristics being: (1) planar direction and height estimation; (2) visualization of sound features according to loudness, continuity, and pitch. The capabilities of the proposed building health monitoring method are verified using environmental sound data acquired at a building in Gunkanjima, which is a world heritage site from Japan.","PeriodicalId":198837,"journal":{"name":"2020 16th International Conference on Distributed Computing in Sensor Systems (DCOSS)","volume":"71 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125946516","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 : 2020-05-01DOI: 10.1109/DCOSS49796.2020.00034
Amitangshu Pal
This paper describes the development of an experimental wireless sensor network (WSN) testbed for studying the nature of irradiance measurements at the sensor nodes that are deployed at different points in the WSN, and oriented differently depending on the deployment geometry. The network was developed on the roof of an academic building at the University of North Carolina at Charlotte (UNC Charlotte), where the sensor nodes are equipped with pyranometer sensors to periodically collect the irradiance measurements at different points and send then to a centralized base station using multi-hop communication. The collected data is analyzed to demonstrate the spatial and temporal variation of energy availability at each individual node, resulting from the localized variations in the light levels.
{"title":"EPIC-RoofNet: A Sensor Network Testbed for Solar Irradiance Measurement and Analysis","authors":"Amitangshu Pal","doi":"10.1109/DCOSS49796.2020.00034","DOIUrl":"https://doi.org/10.1109/DCOSS49796.2020.00034","url":null,"abstract":"This paper describes the development of an experimental wireless sensor network (WSN) testbed for studying the nature of irradiance measurements at the sensor nodes that are deployed at different points in the WSN, and oriented differently depending on the deployment geometry. The network was developed on the roof of an academic building at the University of North Carolina at Charlotte (UNC Charlotte), where the sensor nodes are equipped with pyranometer sensors to periodically collect the irradiance measurements at different points and send then to a centralized base station using multi-hop communication. The collected data is analyzed to demonstrate the spatial and temporal variation of energy availability at each individual node, resulting from the localized variations in the light levels.","PeriodicalId":198837,"journal":{"name":"2020 16th International Conference on Distributed Computing in Sensor Systems (DCOSS)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133540152","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 : 2020-05-01DOI: 10.1109/DCOSS49796.2020.00080
S. Kündig, C. Angelopoulos, S. Kuppannagari, J. Rolim, V. Prasanna
Edge computing established paradigms are prone to implicate solely powerful server-like edge nodes, in static or semi-static topologies, of centrally-controlled edge networks. In this paper, leveraging upon recent technological advancements and trends, we introduce a novel networking paradigm employing resources provided by independent crowd peers, within a zone of local proximity, to establish collaborative networks for edge computing. We call this paradigm the Crowdsourced Edge. We detail the architecture and characteristics of this novel paradigm, highlighting its unique characteristics and specific challenges, while also positioning it vis-a-vis the existing edge computing concretisations. Finally, we demonstrate the Crowdsourced Edge functionality by presenting an ongoing use case regarding a video-enhanced object search.
{"title":"Crowdsourced Edge: A Novel Networking Paradigm for the Collaborative Community","authors":"S. Kündig, C. Angelopoulos, S. Kuppannagari, J. Rolim, V. Prasanna","doi":"10.1109/DCOSS49796.2020.00080","DOIUrl":"https://doi.org/10.1109/DCOSS49796.2020.00080","url":null,"abstract":"Edge computing established paradigms are prone to implicate solely powerful server-like edge nodes, in static or semi-static topologies, of centrally-controlled edge networks. In this paper, leveraging upon recent technological advancements and trends, we introduce a novel networking paradigm employing resources provided by independent crowd peers, within a zone of local proximity, to establish collaborative networks for edge computing. We call this paradigm the Crowdsourced Edge. We detail the architecture and characteristics of this novel paradigm, highlighting its unique characteristics and specific challenges, while also positioning it vis-a-vis the existing edge computing concretisations. Finally, we demonstrate the Crowdsourced Edge functionality by presenting an ongoing use case regarding a video-enhanced object search.","PeriodicalId":198837,"journal":{"name":"2020 16th International Conference on Distributed Computing in Sensor Systems (DCOSS)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133975746","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 : 2020-05-01DOI: 10.1109/DCOSS49796.2020.00031
Emekcan Aras, M. Ammar, Fan Yang, W. Joosen, D. Hughes
The Internet of Things (IoT) is being deployed at large scale in a wide range of long-life applications. Examples range from Industry 4.0 to smart lighting systems. These applications have diverse requirements of non-volatile storage. However, the flash memory that is used in today’s IoT devices offers limited write endurance and must therefore be carefully managed if applications are to deliver on their promises of multiyear lifetimes. Managing the health of flash memory is difficult for application developers, as it requires in-depth hardware and software knowledge, which often needs to the problem being neglected. While various techniques have been proposed to preserve the health of flash memory, prior work tends to focus on a single hardware platform and data type. Furthermore, prior work does not provide lifetime guarantees. This paper tackles this problem by proposing MicroVault, a simple and unified interface for reliable non-volatile data storage on resource-constrained IoT devices. MicroVault enforces developer-specified lifetime guarantees through a range of lifetime extension techniques, which are adaptively applied based upon the needs of the application. Evaluation shows that MicroVault dramatically extends the lifetime of flash memory while minimising overhead.
{"title":"MicroVault: Reliable Storage Unit for IoT Devices","authors":"Emekcan Aras, M. Ammar, Fan Yang, W. Joosen, D. Hughes","doi":"10.1109/DCOSS49796.2020.00031","DOIUrl":"https://doi.org/10.1109/DCOSS49796.2020.00031","url":null,"abstract":"The Internet of Things (IoT) is being deployed at large scale in a wide range of long-life applications. Examples range from Industry 4.0 to smart lighting systems. These applications have diverse requirements of non-volatile storage. However, the flash memory that is used in today’s IoT devices offers limited write endurance and must therefore be carefully managed if applications are to deliver on their promises of multiyear lifetimes. Managing the health of flash memory is difficult for application developers, as it requires in-depth hardware and software knowledge, which often needs to the problem being neglected. While various techniques have been proposed to preserve the health of flash memory, prior work tends to focus on a single hardware platform and data type. Furthermore, prior work does not provide lifetime guarantees. This paper tackles this problem by proposing MicroVault, a simple and unified interface for reliable non-volatile data storage on resource-constrained IoT devices. MicroVault enforces developer-specified lifetime guarantees through a range of lifetime extension techniques, which are adaptively applied based upon the needs of the application. Evaluation shows that MicroVault dramatically extends the lifetime of flash memory while minimising overhead.","PeriodicalId":198837,"journal":{"name":"2020 16th International Conference on Distributed Computing in Sensor Systems (DCOSS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129913404","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 : 2020-05-01DOI: 10.1109/DCOSS49796.2020.00065
Sumali S. Morapitiya, Mohammad Furqan Ali, S. Rajkumar, S. Wijayasekara, D. Jayakody, R. Weerasuriya
Simultaneous Wireless Information and Power Transfer (SWIPT) technique is introduced in Radio Frequency (RF) communication to carry both information and power in same medium. In this approach, the energy can be harvested while decoding the information carries in an RF wave. Recently, the same concept applied in Visible Light Communication (VLC) namely Simultaneous Light Wave Information and Power Transfer (SLIPT), which is highly recommended in an indoor applications to overcome the problem facing in RF communication. Thus, SLIPT is introduced to transmit the power through a Light Emitting Diode (LED) luminaries. In this work, we compare both SWIPT and SLIPT technologies and realize SLIPT technology archives increased performance in terms of the amount of harvested energy, outage probability and error rate performance.
{"title":"A SLIPT-assisted Visible Light Communication Scheme","authors":"Sumali S. Morapitiya, Mohammad Furqan Ali, S. Rajkumar, S. Wijayasekara, D. Jayakody, R. Weerasuriya","doi":"10.1109/DCOSS49796.2020.00065","DOIUrl":"https://doi.org/10.1109/DCOSS49796.2020.00065","url":null,"abstract":"Simultaneous Wireless Information and Power Transfer (SWIPT) technique is introduced in Radio Frequency (RF) communication to carry both information and power in same medium. In this approach, the energy can be harvested while decoding the information carries in an RF wave. Recently, the same concept applied in Visible Light Communication (VLC) namely Simultaneous Light Wave Information and Power Transfer (SLIPT), which is highly recommended in an indoor applications to overcome the problem facing in RF communication. Thus, SLIPT is introduced to transmit the power through a Light Emitting Diode (LED) luminaries. In this work, we compare both SWIPT and SLIPT technologies and realize SLIPT technology archives increased performance in terms of the amount of harvested energy, outage probability and error rate performance.","PeriodicalId":198837,"journal":{"name":"2020 16th International Conference on Distributed Computing in Sensor Systems (DCOSS)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129424824","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 : 2020-05-01DOI: 10.1109/DCOSS49796.2020.00030
Shengrong Yin, A. Pokhrel, Milad Heydariaan, O. Gnawali, L. Thapa, S. Regmi, Dhiraj Pokhrel
Clean Cooking is essential to maintain a healthy lifestyle. However, many people in developing economies do not have access to clean cooking. To promote clean cooking, first, we need to understand the cooking patterns in the household, and second, design interventions over those patterns. We also need to understand the grid and power supply readiness to support electricity-based clean cooking initiatives. In this paper, we provide an affordable and scalable energy monitoring system solution to instrument the cooking pattern in peri-urban Nepal. Our design consists of off-the-shelf power meters, minor changes in sockets/wiring at homes, data upload using cellular radio, and standard dashboard and analysis in the cloud. We deployed the system in 35 households in peri-urban Nepal and collected data from early August until the middle of October 2019. Our preliminary study indicates: 1) Cellular data access is a viable way to upload instrumentation data to the Internet in studies of this nature. 2) Data integrity and reliability are closely coupled with user behaviors and cellular reliability. 3) Deployment can be centralized instead of distributed, and cost can be affordable. 4) Continuous data collection from about three months shows poor power quality in the area.
{"title":"Instrumentation for Cooking Pattern Analysis in Peri-Urban Nepal","authors":"Shengrong Yin, A. Pokhrel, Milad Heydariaan, O. Gnawali, L. Thapa, S. Regmi, Dhiraj Pokhrel","doi":"10.1109/DCOSS49796.2020.00030","DOIUrl":"https://doi.org/10.1109/DCOSS49796.2020.00030","url":null,"abstract":"Clean Cooking is essential to maintain a healthy lifestyle. However, many people in developing economies do not have access to clean cooking. To promote clean cooking, first, we need to understand the cooking patterns in the household, and second, design interventions over those patterns. We also need to understand the grid and power supply readiness to support electricity-based clean cooking initiatives. In this paper, we provide an affordable and scalable energy monitoring system solution to instrument the cooking pattern in peri-urban Nepal. Our design consists of off-the-shelf power meters, minor changes in sockets/wiring at homes, data upload using cellular radio, and standard dashboard and analysis in the cloud. We deployed the system in 35 households in peri-urban Nepal and collected data from early August until the middle of October 2019. Our preliminary study indicates: 1) Cellular data access is a viable way to upload instrumentation data to the Internet in studies of this nature. 2) Data integrity and reliability are closely coupled with user behaviors and cellular reliability. 3) Deployment can be centralized instead of distributed, and cost can be affordable. 4) Continuous data collection from about three months shows poor power quality in the area.","PeriodicalId":198837,"journal":{"name":"2020 16th International Conference on Distributed Computing in Sensor Systems (DCOSS)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114143466","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 : 2020-05-01DOI: 10.1109/DCOSS49796.2020.00082
Anastasia Vayona, G. Demetriou
In this paper we explore the social dimension of sustainability in Circular Economy. Considering that the three known pillars of sustainability (social, environmental and economic) may have competing agendas and priorities, we argue that Circular Economy has a potential to act as a mitigation mechanism and offer a common ground so that these orthogonal pillars will be able to coexist in a corporate setting. We conject that attribution is a key concept in understanding the antecedents and factors affecting the adoption of Circular Economy strategies and policies within an organization. Following a review of the current state of research in attribution theory, we develop an operating model proposition in the context of Circular Economy.
{"title":"Towards An Operating Model For Attribution In Circular Economy","authors":"Anastasia Vayona, G. Demetriou","doi":"10.1109/DCOSS49796.2020.00082","DOIUrl":"https://doi.org/10.1109/DCOSS49796.2020.00082","url":null,"abstract":"In this paper we explore the social dimension of sustainability in Circular Economy. Considering that the three known pillars of sustainability (social, environmental and economic) may have competing agendas and priorities, we argue that Circular Economy has a potential to act as a mitigation mechanism and offer a common ground so that these orthogonal pillars will be able to coexist in a corporate setting. We conject that attribution is a key concept in understanding the antecedents and factors affecting the adoption of Circular Economy strategies and policies within an organization. Following a review of the current state of research in attribution theory, we develop an operating model proposition in the context of Circular Economy.","PeriodicalId":198837,"journal":{"name":"2020 16th International Conference on Distributed Computing in Sensor Systems (DCOSS)","volume":"59 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121525942","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 : 2020-05-01DOI: 10.1109/DCOSS49796.2020.00046
G. Filios, Ioannis Katsidimas, S. Nikoletseas, Stefanos H. Panagiotou, Theofanis P. Raptis
As data awareness in manufacturing companies increases with the deployment of sensors and Internet of Things (IoT) devices, data-driven maintenance and prediction have become quite popular in the Industry 4.0 paradigm. Machine Learning (ML) has been recognised as a promising, efficient and reliable tool for fault detection use cases, as it allows to export important knowledge from monitored assets. Scientists deal with issues such as the small amount of data that indicate potential problems, or the imbalance which exists between the standard process data and the data inadequacy of the systems to make a high precision forecast. Currently, in this context, even large industries are not able to effectively predict abnormal behaviors in their tools, processes and equipment, when adopting strategies to anticipate crucial events. In this paper, we propose a methodology to enable prediction of a packing machine’s stoppages in manufacturing process of a large industry, by using forecasting techniques based on univariate time series data. There are more than 100 reasons that cause the machine to stop, in a quite big production line length. However, we use a single signal, concerning the machines operational status to make our prediction, without considering other fault or warning signals, hence its characterization as "agnostic". A workflow is presented for cleaning and preprocessing the data, and for training and evaluating a predictive model. Two predictive models, namely ARIMA and Prophet, are applied and evaluated on real data from an advanced machining process used for packing. Training and evaluation tests indicate that the results of the applied methods perform well on a daily basis. Our work can be further extended and act as reference for future research activities that could lead to more robust and accurate prediction frameworks.
{"title":"An Agnostic Data-Driven Approach to Predict Stoppages of Industrial Packing Machine in Near","authors":"G. Filios, Ioannis Katsidimas, S. Nikoletseas, Stefanos H. Panagiotou, Theofanis P. Raptis","doi":"10.1109/DCOSS49796.2020.00046","DOIUrl":"https://doi.org/10.1109/DCOSS49796.2020.00046","url":null,"abstract":"As data awareness in manufacturing companies increases with the deployment of sensors and Internet of Things (IoT) devices, data-driven maintenance and prediction have become quite popular in the Industry 4.0 paradigm. Machine Learning (ML) has been recognised as a promising, efficient and reliable tool for fault detection use cases, as it allows to export important knowledge from monitored assets. Scientists deal with issues such as the small amount of data that indicate potential problems, or the imbalance which exists between the standard process data and the data inadequacy of the systems to make a high precision forecast. Currently, in this context, even large industries are not able to effectively predict abnormal behaviors in their tools, processes and equipment, when adopting strategies to anticipate crucial events. In this paper, we propose a methodology to enable prediction of a packing machine’s stoppages in manufacturing process of a large industry, by using forecasting techniques based on univariate time series data. There are more than 100 reasons that cause the machine to stop, in a quite big production line length. However, we use a single signal, concerning the machines operational status to make our prediction, without considering other fault or warning signals, hence its characterization as \"agnostic\". A workflow is presented for cleaning and preprocessing the data, and for training and evaluating a predictive model. Two predictive models, namely ARIMA and Prophet, are applied and evaluated on real data from an advanced machining process used for packing. Training and evaluation tests indicate that the results of the applied methods perform well on a daily basis. Our work can be further extended and act as reference for future research activities that could lead to more robust and accurate prediction frameworks.","PeriodicalId":198837,"journal":{"name":"2020 16th International Conference on Distributed Computing in Sensor Systems (DCOSS)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114358914","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 : 2020-05-01DOI: 10.1109/DCOSS49796.2020.00071
Klitos Christodoulou, Panayiotis Christodoulou, Z. Zinonos, E. Carayannis, S. Chatzichristofis
The COVID-19 pandemic is stress-testing existing health information exchange systems. There exists an increasing demand for sharing patient information and efficiently responding to patient medial data requests. Current health information technologies lack data fluidity, especially for remotely sharing medical data beyond their protected, local data storage. This paper presents a blockchain-based data-sharing framework that leverages the properties of immutability and decentralization to ensure a secure, user-centric approach for accessing and controlling access to sensitive medical data. The proposed framework builds its foundations on a peer-to-peer network fueled by the distributed InterPlanetary File System combined with on-chain tagging, and on the use of cryptographic generation techniques for enabling a secure way of sharing medical data. The flow of information is orchestrated by a smart-contract deployed on a blockchain-based protocol to ensure traceability and data integrity. The effectiveness of the framework is demonstrated with the implementation of the framework over a pilot study.
{"title":"Health Information Exchange with Blockchain amid Covid-19-like Pandemics","authors":"Klitos Christodoulou, Panayiotis Christodoulou, Z. Zinonos, E. Carayannis, S. Chatzichristofis","doi":"10.1109/DCOSS49796.2020.00071","DOIUrl":"https://doi.org/10.1109/DCOSS49796.2020.00071","url":null,"abstract":"The COVID-19 pandemic is stress-testing existing health information exchange systems. There exists an increasing demand for sharing patient information and efficiently responding to patient medial data requests. Current health information technologies lack data fluidity, especially for remotely sharing medical data beyond their protected, local data storage. This paper presents a blockchain-based data-sharing framework that leverages the properties of immutability and decentralization to ensure a secure, user-centric approach for accessing and controlling access to sensitive medical data. The proposed framework builds its foundations on a peer-to-peer network fueled by the distributed InterPlanetary File System combined with on-chain tagging, and on the use of cryptographic generation techniques for enabling a secure way of sharing medical data. The flow of information is orchestrated by a smart-contract deployed on a blockchain-based protocol to ensure traceability and data integrity. The effectiveness of the framework is demonstrated with the implementation of the framework over a pilot study.","PeriodicalId":198837,"journal":{"name":"2020 16th International Conference on Distributed Computing in Sensor Systems (DCOSS)","volume":"286 ","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114093877","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 : 2020-05-01DOI: 10.1109/DCOSS49796.2020.00055
Marlene Böhmer, Andreas Schmidt, Pablo Gil Pereira, T. Herfet
In order to create cooperating swarms of Unmanned Autonomous Vehicles (UAVs) that also interact with various other systems and devices, open and free communication systems are mandatory. This paper presents an implementation of such a communication system to incorporate the Crazyflie nano-drone as a UAV platform. The protocol stack leverages the open Predictably Reliable Real-time Transport (PRRT) protocol that adds latency-awareness and -predictability to stacks composed of standard Internet protocols. To enable the drone to receive and reply to control commands via Wi-Fi, it has been extended with a Raspberry Pi that runs two variants of the Crazybridge—a software to connect the control board to the network. To evaluate how practical this solution is for the use in control applications, the communication has been analysed with a focus on the latency properties. Our investigations show that despite using the open protocol stack—and hence opting out of specialised implementations—the resulting latencies are in the same order of magnitude (4 to 9 ms) as the latency of the proprietary link.
{"title":"Latency-aware and -predictable Communication with Open Protocol Stacks for Remote Drone Control","authors":"Marlene Böhmer, Andreas Schmidt, Pablo Gil Pereira, T. Herfet","doi":"10.1109/DCOSS49796.2020.00055","DOIUrl":"https://doi.org/10.1109/DCOSS49796.2020.00055","url":null,"abstract":"In order to create cooperating swarms of Unmanned Autonomous Vehicles (UAVs) that also interact with various other systems and devices, open and free communication systems are mandatory. This paper presents an implementation of such a communication system to incorporate the Crazyflie nano-drone as a UAV platform. The protocol stack leverages the open Predictably Reliable Real-time Transport (PRRT) protocol that adds latency-awareness and -predictability to stacks composed of standard Internet protocols. To enable the drone to receive and reply to control commands via Wi-Fi, it has been extended with a Raspberry Pi that runs two variants of the Crazybridge—a software to connect the control board to the network. To evaluate how practical this solution is for the use in control applications, the communication has been analysed with a focus on the latency properties. Our investigations show that despite using the open protocol stack—and hence opting out of specialised implementations—the resulting latencies are in the same order of magnitude (4 to 9 ms) as the latency of the proprietary link.","PeriodicalId":198837,"journal":{"name":"2020 16th International Conference on Distributed Computing in Sensor Systems (DCOSS)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130655754","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：