Pub Date : 2014-04-15DOI: 10.1109/IPSN.2014.6846789
H. Smeets, Chia-Yen Shih, Tim Meurer, P. Marrón
Node reprogramming serves as an important service to support post-deployment code management and maintenance for unattended wireless sensor networks or autonomous robotics applications. We present a prototype of a design framework called SHAMPU, a Single chip Host for Autonomous Mote Programming over USB. A SHAMPU device is portable and can be paired with a sensor node for post-deployment reprogramming that is OS independent. Moreover, it is small, lightweight and energy efficient. In the demo, we will present two scenarios, in which SHAMPU-paired Telosbs are integrated with a mobile flying robot and locomotives for local autonomous reprogramming by the flying robot and for network reprogramming with code dissemination via the data links on the tracks, respectively.
{"title":"Demonstration abstract: A lightweight, portable device with integrated USB-Host support for reprogramming wireless sensor nodes","authors":"H. Smeets, Chia-Yen Shih, Tim Meurer, P. Marrón","doi":"10.1109/IPSN.2014.6846789","DOIUrl":"https://doi.org/10.1109/IPSN.2014.6846789","url":null,"abstract":"Node reprogramming serves as an important service to support post-deployment code management and maintenance for unattended wireless sensor networks or autonomous robotics applications. We present a prototype of a design framework called SHAMPU, a Single chip Host for Autonomous Mote Programming over USB. A SHAMPU device is portable and can be paired with a sensor node for post-deployment reprogramming that is OS independent. Moreover, it is small, lightweight and energy efficient. In the demo, we will present two scenarios, in which SHAMPU-paired Telosbs are integrated with a mobile flying robot and locomotives for local autonomous reprogramming by the flying robot and for network reprogramming with code dissemination via the data links on the tracks, respectively.","PeriodicalId":297218,"journal":{"name":"IPSN-14 Proceedings of the 13th International Symposium on Information Processing in Sensor Networks","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128477173","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 : 2014-04-15DOI: 10.1109/IPSN.2014.6846761
M. Mousa, C. Claudel
This article describes a machine learning approach to water level estimation in a dual ultrasonic/passive infrared urban flood sensor system. We first show that an ultrasonic rangefinder alone is unable to accurately measure the level of water on a road due to thermal effects. Using additional passive infrared sensors, we show that ground temperature and local sensor temperature measurements are sufficient to correct the rangefinder readings and improve the flood detection performance. Since floods occur very rarely, we use a supervised learning approach to estimate the correction to the ultrasonic rangefinder caused by temperature fluctuations. Preliminary data shows that water level can be estimated with an absolute error of less than 2 cm.
{"title":"Poster abstract: Water level estimation in urban ultrasonic/passive infrared flash flood sensor networks using supervised learning","authors":"M. Mousa, C. Claudel","doi":"10.1109/IPSN.2014.6846761","DOIUrl":"https://doi.org/10.1109/IPSN.2014.6846761","url":null,"abstract":"This article describes a machine learning approach to water level estimation in a dual ultrasonic/passive infrared urban flood sensor system. We first show that an ultrasonic rangefinder alone is unable to accurately measure the level of water on a road due to thermal effects. Using additional passive infrared sensors, we show that ground temperature and local sensor temperature measurements are sufficient to correct the rangefinder readings and improve the flood detection performance. Since floods occur very rarely, we use a supervised learning approach to estimate the correction to the ultrasonic rangefinder caused by temperature fluctuations. Preliminary data shows that water level can be estimated with an absolute error of less than 2 cm.","PeriodicalId":297218,"journal":{"name":"IPSN-14 Proceedings of the 13th International Symposium on Information Processing in Sensor Networks","volume":"351 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132529653","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 : 2014-04-15DOI: 10.1109/IPSN.2014.6846763
Shaohan Hu, Lu Su, Shen Li, Shiguang Wang, Chenji Pan, Siyu Gu, Md. Tanvir Al Amin, Hengchang Liu, Suman Nath, Romit Roy Choudhury, T. Abdelzaher
We present eNav, a smartphone-based vehicular GPS navigation system that has an energy-saving location sensing mode capable of drastically reducing navigation energy needs. Traditional implementations sample the phone GPS at the highest possible rate (usually 1Hz) to ensure constant highest possible localization accuracy. This practice results in excessive phone battery consumption and reduces the attainable length of a navigation session. The seemingly most common solution would be to always use a car-charger and keep the phone plugged-in during navigation at all times. However, according to a comprehensive survey we conducted, only a small percent of people would actually always carry around their phones' car-chargers and cables, as doing so is inconvenient and defeats the true “wireless” nature of mobile phones. In addressing this problem, eNav exploits the phone's lower-energy on-board motion sensors for approximate location sensing when the vehicle is sufficiently far from the next navigation waypoint, using actual GPS sampling only when close. Our user study shows that, while remaining virtually transparent to users, eNav can reduce navigation energy consumption by over 80% without compromising navigation quality or user experience.
{"title":"Poster abstract: ENav — A smartphone-based energy efficient vehicular navigation system","authors":"Shaohan Hu, Lu Su, Shen Li, Shiguang Wang, Chenji Pan, Siyu Gu, Md. Tanvir Al Amin, Hengchang Liu, Suman Nath, Romit Roy Choudhury, T. Abdelzaher","doi":"10.1109/IPSN.2014.6846763","DOIUrl":"https://doi.org/10.1109/IPSN.2014.6846763","url":null,"abstract":"We present eNav, a smartphone-based vehicular GPS navigation system that has an energy-saving location sensing mode capable of drastically reducing navigation energy needs. Traditional implementations sample the phone GPS at the highest possible rate (usually 1Hz) to ensure constant highest possible localization accuracy. This practice results in excessive phone battery consumption and reduces the attainable length of a navigation session. The seemingly most common solution would be to always use a car-charger and keep the phone plugged-in during navigation at all times. However, according to a comprehensive survey we conducted, only a small percent of people would actually always carry around their phones' car-chargers and cables, as doing so is inconvenient and defeats the true “wireless” nature of mobile phones. In addressing this problem, eNav exploits the phone's lower-energy on-board motion sensors for approximate location sensing when the vehicle is sufficiently far from the next navigation waypoint, using actual GPS sampling only when close. Our user study shows that, while remaining virtually transparent to users, eNav can reduce navigation energy consumption by over 80% without compromising navigation quality or user experience.","PeriodicalId":297218,"journal":{"name":"IPSN-14 Proceedings of the 13th International Symposium on Information Processing in Sensor Networks","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115096552","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 : 2014-04-15DOI: 10.1109/IPSN.2014.6846745
Robert F. Dickerson, Enamul Hoque, Philip Asare, S. Nirjon, J. Stankovic
Home monitoring systems currently gather information about peoples activities of daily living and information regarding emergencies, however they currently lack the ability to track speech. Practical speech analysis solutions are needed to help monitor ongoing conditions such as depression, as the amount of social interaction and vocal affect is important for assessing mood and well-being. Although there are existing solutions that classify the identity and the mood of a speaker, when the acoustic signals are captured in reverberant environments they perform poorly. In this paper, we present a practical reverberation compensation method called RESONATE, which uses simulated room impulse responses to adapt a training corpus for use in multiple real reverberant rooms. We demonstrate that the system creates robust classifiers that perform within 5 - 10% of baseline accuracy of non-reverberant environments. We demonstrate and evaluate the performance of this matched condition strategy using a public dataset, and also in controlled experiments with six rooms, and two long-term and uncontrolled real deployments. We offer a practical implementation that performs collection, feature extraction, and classification on-node, and training and simulation of training sets on a base station or cloud service.
{"title":"RESONATE: Reverberation environment simulation for improved classification of speech models","authors":"Robert F. Dickerson, Enamul Hoque, Philip Asare, S. Nirjon, J. Stankovic","doi":"10.1109/IPSN.2014.6846745","DOIUrl":"https://doi.org/10.1109/IPSN.2014.6846745","url":null,"abstract":"Home monitoring systems currently gather information about peoples activities of daily living and information regarding emergencies, however they currently lack the ability to track speech. Practical speech analysis solutions are needed to help monitor ongoing conditions such as depression, as the amount of social interaction and vocal affect is important for assessing mood and well-being. Although there are existing solutions that classify the identity and the mood of a speaker, when the acoustic signals are captured in reverberant environments they perform poorly. In this paper, we present a practical reverberation compensation method called RESONATE, which uses simulated room impulse responses to adapt a training corpus for use in multiple real reverberant rooms. We demonstrate that the system creates robust classifiers that perform within 5 - 10% of baseline accuracy of non-reverberant environments. We demonstrate and evaluate the performance of this matched condition strategy using a public dataset, and also in controlled experiments with six rooms, and two long-term and uncontrolled real deployments. We offer a practical implementation that performs collection, feature extraction, and classification on-node, and training and simulation of training sets on a base station or cloud service.","PeriodicalId":297218,"journal":{"name":"IPSN-14 Proceedings of the 13th International Symposium on Information Processing in Sensor Networks","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123905714","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 : 2014-04-15DOI: 10.1109/IPSN.2014.6846780
A. Azzara, Daniele Alessandrelli, M. Petracca, P. Pagano
PyoT is a web-based framework designed to simplify the development of complex applications for the IoT. Adopting the macroprogramming paradigm, it lets the programmers focus on the global application's goal, hiding low-level communication details. Developers can easily define, test, and share applications using IPython Notebooks or through a rich Web interface. The framework is capable of efficiently distributing the processing effort inside the network. This demonstration shows some of the features of PyoT, such as programming groups of nodes as a whole, creating in-network tasks, monitoring sensors, and visualizing network information. PyoT is available for download and testing on real WSN deployments or in emulated environments.
{"title":"Demonstration abstract: PyoT, a macroprogramming framework for the IoT","authors":"A. Azzara, Daniele Alessandrelli, M. Petracca, P. Pagano","doi":"10.1109/IPSN.2014.6846780","DOIUrl":"https://doi.org/10.1109/IPSN.2014.6846780","url":null,"abstract":"PyoT is a web-based framework designed to simplify the development of complex applications for the IoT. Adopting the macroprogramming paradigm, it lets the programmers focus on the global application's goal, hiding low-level communication details. Developers can easily define, test, and share applications using IPython Notebooks or through a rich Web interface. The framework is capable of efficiently distributing the processing effort inside the network. This demonstration shows some of the features of PyoT, such as programming groups of nodes as a whole, creating in-network tasks, monitoring sensors, and visualizing network information. PyoT is available for download and testing on real WSN deployments or in emulated environments.","PeriodicalId":297218,"journal":{"name":"IPSN-14 Proceedings of the 13th International Symposium on Information Processing in Sensor Networks","volume":"62 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121361076","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 : 2014-04-15DOI: 10.1109/IPSN.2014.6846768
Liqiong Chang, Dingyi Fang, Zhe Yang, Xiaojiang Chen, Ju Wang, Weike Nie, Tianzhang Xing
Most previous Device-free Passive Localization (DFL) methods are learning based and they assume the distribution of Received Radio Signal (RSS) distorted by an object is fixed across time. However, the signals significantly vary over time and the pre-obtained radio map (or prior knowledge) outdated in the localization phase, thus causing the localization accuracy decrease. To cope with this problem, this poster proposes, EIL, an environment-independent DFL approach which can improve the system robustness and localization accuracy by eliminating the interference of environment on RSS over time in both the training phase and the localization phase. Through both the extensive experiments and simulations, EIL keeps a range of 0.5m to 0.6m localization errors for 90% locations over time.
{"title":"Poster abstract: EIL — An environment-independent Device-free Passive Localization approach","authors":"Liqiong Chang, Dingyi Fang, Zhe Yang, Xiaojiang Chen, Ju Wang, Weike Nie, Tianzhang Xing","doi":"10.1109/IPSN.2014.6846768","DOIUrl":"https://doi.org/10.1109/IPSN.2014.6846768","url":null,"abstract":"Most previous Device-free Passive Localization (DFL) methods are learning based and they assume the distribution of Received Radio Signal (RSS) distorted by an object is fixed across time. However, the signals significantly vary over time and the pre-obtained radio map (or prior knowledge) outdated in the localization phase, thus causing the localization accuracy decrease. To cope with this problem, this poster proposes, EIL, an environment-independent DFL approach which can improve the system robustness and localization accuracy by eliminating the interference of environment on RSS over time in both the training phase and the localization phase. Through both the extensive experiments and simulations, EIL keeps a range of 0.5m to 0.6m localization errors for 90% locations over time.","PeriodicalId":297218,"journal":{"name":"IPSN-14 Proceedings of the 13th International Symposium on Information Processing in Sensor Networks","volume":"266 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116422874","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 : 2014-04-15DOI: 10.1109/IPSN.2014.6846758
Naveed Anwar Bhatti, A. Syed, Muhammad Hamad Alizai
We present here a first prac architecture that allows us to decouple en activities in WSN. Such a separation of us to utilize abundant energy sources d location, allowing unrestricted lifetime energy consumption in WSN. We demons practical decoupling using low-cost and -beaming that powers current WSN platf We design and implement LAMP: a tiered energy supply to both mesh and clust using an energy distribution protocol. W show that, for an additional cost of $2 support perpetual mesh functionality for nodes in clustered operation.
{"title":"Sensors with lasers: Building a WSN power grid","authors":"Naveed Anwar Bhatti, A. Syed, Muhammad Hamad Alizai","doi":"10.1109/IPSN.2014.6846758","DOIUrl":"https://doi.org/10.1109/IPSN.2014.6846758","url":null,"abstract":"We present here a first prac architecture that allows us to decouple en activities in WSN. Such a separation of us to utilize abundant energy sources d location, allowing unrestricted lifetime energy consumption in WSN. We demons practical decoupling using low-cost and -beaming that powers current WSN platf We design and implement LAMP: a tiered energy supply to both mesh and clust using an energy distribution protocol. W show that, for an additional cost of $2 support perpetual mesh functionality for nodes in clustered operation.","PeriodicalId":297218,"journal":{"name":"IPSN-14 Proceedings of the 13th International Symposium on Information Processing in Sensor Networks","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123573256","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 : 2014-04-15DOI: 10.1109/IPSN.2014.6846795
Meghan Clark, Bradford Campbell, P. Dutta
Detailed breakdowns of household energy consumption allow occupants to better understand their energy usage patterns and identify opportunities for energy savings. Current solutions are costly, invasive, and difficult to maintain. Sub-metering approaches rely on - and are hindered by - complex hardware. To address these problems, we demonstrate a sub-metering system that can estimate the power draw of individual loads by augmenting aggregate measurements with very simple sensors. These sensors wake up at a frequency proportional to the power draw of a neighboring load, and report these wakeups to a central server. We model the relationship between each sensor's wakeup frequency and the load's power draw as a monotonically increasing polynomial. We calibrate each sensor's function by constructing a linear least squares problem that allows us to discover the set of polynomial coefficients that minimize the difference between the estimated power draw and the power draw as derived from the aggregate measurements. After calibration, we can convert sensor wakeup frequencies to power draw in real time. This systems approach to sub-metering results in deployments that are easy to install and maintain, allowing users to gain a broad yet detailed view of their energy consumption and costs.
{"title":"Demonstration abstract: Submetering by synthesizing side-channel sensor streams","authors":"Meghan Clark, Bradford Campbell, P. Dutta","doi":"10.1109/IPSN.2014.6846795","DOIUrl":"https://doi.org/10.1109/IPSN.2014.6846795","url":null,"abstract":"Detailed breakdowns of household energy consumption allow occupants to better understand their energy usage patterns and identify opportunities for energy savings. Current solutions are costly, invasive, and difficult to maintain. Sub-metering approaches rely on - and are hindered by - complex hardware. To address these problems, we demonstrate a sub-metering system that can estimate the power draw of individual loads by augmenting aggregate measurements with very simple sensors. These sensors wake up at a frequency proportional to the power draw of a neighboring load, and report these wakeups to a central server. We model the relationship between each sensor's wakeup frequency and the load's power draw as a monotonically increasing polynomial. We calibrate each sensor's function by constructing a linear least squares problem that allows us to discover the set of polynomial coefficients that minimize the difference between the estimated power draw and the power draw as derived from the aggregate measurements. After calibration, we can convert sensor wakeup frequencies to power draw in real time. This systems approach to sub-metering results in deployments that are easy to install and maintain, allowing users to gain a broad yet detailed view of their energy consumption and costs.","PeriodicalId":297218,"journal":{"name":"IPSN-14 Proceedings of the 13th International Symposium on Information Processing in Sensor Networks","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114711405","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 : 2014-04-15DOI: 10.1109/IPSN.2014.6846738
Ashish Kapoor, Zachary Horvitz, S. Laube, E. Horvitz
We explore the feasibility of using commercial aircraft as sensors for observing weather phenomena at a continental scale. We focus specifically on the problem of wind forecasting and explore the use of machine learning and inference methods to harness air and ground speeds reported by aircraft at different locations and altitudes. We validate the learned predictive model with a field study where we release an instrumented high-altitude balloon and compare the predicted trajectory with the sensed winds. The experiments show the promise of using airplane in flight as a large-scale sensor network. Beyond making predictions, we explore the guidance of sensing with value-of-information analyses, where we consider uncertainties and needs of sets of routes and maximize information value in light of the costs of acquiring data from airplanes. The methods can be used to select ideal subsets of planes to serve as sensors and also to evaluate the value of requesting shifts in trajectories of flights for sensing.
{"title":"Airplanes aloft as a sensor network for wind forecasting","authors":"Ashish Kapoor, Zachary Horvitz, S. Laube, E. Horvitz","doi":"10.1109/IPSN.2014.6846738","DOIUrl":"https://doi.org/10.1109/IPSN.2014.6846738","url":null,"abstract":"We explore the feasibility of using commercial aircraft as sensors for observing weather phenomena at a continental scale. We focus specifically on the problem of wind forecasting and explore the use of machine learning and inference methods to harness air and ground speeds reported by aircraft at different locations and altitudes. We validate the learned predictive model with a field study where we release an instrumented high-altitude balloon and compare the predicted trajectory with the sensed winds. The experiments show the promise of using airplane in flight as a large-scale sensor network. Beyond making predictions, we explore the guidance of sensing with value-of-information analyses, where we consider uncertainties and needs of sets of routes and maximize information value in light of the costs of acquiring data from airplanes. The methods can be used to select ideal subsets of planes to serve as sensors and also to evaluate the value of requesting shifts in trajectories of flights for sensing.","PeriodicalId":297218,"journal":{"name":"IPSN-14 Proceedings of the 13th International Symposium on Information Processing in Sensor Networks","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129380837","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 : 2014-04-15DOI: 10.1109/IPSN.2014.6846736
Maxim Buevich, Dan Schnitzer, Tristan Escalada, Arthur Jacquiau-Chamski, Anthony G. Rowe
In this paper, we present the architecture, design and experiences from a wirelessly managed microgrid deployment in rural Les Anglais, Haiti. The system consists of a three-tiered architecture with a cloud-based monitoring and control service, a local embedded gateway infrastructure and a mesh network of wireless smart meters deployed at 52 buildings. Each smart meter device has an 802.15.4 radio that enables remote monitoring and control of electrical service. The meters communicate over a scalable multi-hop TDMA network back to a central gateway that manages load within the system. The gateway also provides an 802.11 interface for an on-site operator and a cellular modem connection to a cloud-backend that manages and stores billing and usage data. The cloud backend allows occupants in each home to pre-pay for electricity at a particular peak power limit using a text messaging service. The system activates each meter within seconds and locally enforces power limits with provisioning for theft detection. We believe that this fine-grained micro-payment model can enable sustainable power in otherwise unfeasible areas. This paper provides a chronology of our deployment and installation strategy that involved GPS-based site mapping along with various network conditioning actions required as the network evolved. Finally, we summarize key lessons learned and hypothesis about additional hardware that could be used to ease the tracing of faults like short circuits and downed lines within microgrids.
{"title":"Fine-grained remote monitoring, control and pre-paid electrical service in rural microgrids","authors":"Maxim Buevich, Dan Schnitzer, Tristan Escalada, Arthur Jacquiau-Chamski, Anthony G. Rowe","doi":"10.1109/IPSN.2014.6846736","DOIUrl":"https://doi.org/10.1109/IPSN.2014.6846736","url":null,"abstract":"In this paper, we present the architecture, design and experiences from a wirelessly managed microgrid deployment in rural Les Anglais, Haiti. The system consists of a three-tiered architecture with a cloud-based monitoring and control service, a local embedded gateway infrastructure and a mesh network of wireless smart meters deployed at 52 buildings. Each smart meter device has an 802.15.4 radio that enables remote monitoring and control of electrical service. The meters communicate over a scalable multi-hop TDMA network back to a central gateway that manages load within the system. The gateway also provides an 802.11 interface for an on-site operator and a cellular modem connection to a cloud-backend that manages and stores billing and usage data. The cloud backend allows occupants in each home to pre-pay for electricity at a particular peak power limit using a text messaging service. The system activates each meter within seconds and locally enforces power limits with provisioning for theft detection. We believe that this fine-grained micro-payment model can enable sustainable power in otherwise unfeasible areas. This paper provides a chronology of our deployment and installation strategy that involved GPS-based site mapping along with various network conditioning actions required as the network evolved. Finally, we summarize key lessons learned and hypothesis about additional hardware that could be used to ease the tracing of faults like short circuits and downed lines within microgrids.","PeriodicalId":297218,"journal":{"name":"IPSN-14 Proceedings of the 13th International Symposium on Information Processing in Sensor Networks","volume":"120 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117297584","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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