Proceedings of the ACM SIGCOMM Workshop on Networked Sensing Systems for a Sustainable Society最新文献

On the prediction of air quality within vehicles using outdoor air pollution: sensors and machine learning algorithms 利用室外空气污染预测车内空气质量:传感器和机器学习算法

Proceedings of the ACM SIGCOMM Workshop on Networked Sensing Systems for a Sustainable Society Pub Date : 2022-08-22 DOI: 10.1145/3538393.3544934

Thomas Baldi, Giovanni Delnevo, Roberto Girau, S. Mirri

引用次数: 4

Kaala

Proceedings of the ACM SIGCOMM Workshop on Networked Sensing Systems for a Sustainable Society Pub Date : 2022-08-22 DOI: 10.1145/3538393.3544937

Udhaya Kumar Dayalan, Rostand A. K. Fezeu, T. Salo, Zhi-Li Zhang

引用次数: 3

An instance-based deep transfer learning approach for resource-constrained environments 资源受限环境下基于实例的深度迁移学习方法

Proceedings of the ACM SIGCOMM Workshop on Networked Sensing Systems for a Sustainable Society Pub Date : 2022-08-22 DOI: 10.1145/3538393.3544938

Gibson Kimutai, Anna Förster

{"title":"An instance-based deep transfer learning approach for resource-constrained environments","authors":"Gibson Kimutai, Anna Förster","doi":"10.1145/3538393.3544938","DOIUrl":"https://doi.org/10.1145/3538393.3544938","url":null,"abstract":"Although Deep Learning (DL) is revolutionising practices across fields, it requires a large amount of data and computing resources, requires considerable training time, and is thus expensive. This study proposes a transfer learning approach by adopting a simplified version of a standard Convolution Neural Network (CNN), which is successful in another domain. We explored three transfer learning approaches: freezing all layers except the first and the last layer of the CNN model, which we had modified, freezing the first layer, updating the weights of the rest of the layers, and fine-tuning the entire network. Furthermore, we trained a DL model from scratch to act as a baseline. We performed the experiments on the Edge Impulse platform. We evaluated the models based on plant-village, tea diseases and land use datasets. Fine-tuning and training the whole network produced the best precision, accuracy, recall, f-measure and sensitivity across the datasets. All three transfer learning schemes significantly reduced the training by more than half. Further, we deployed the fine-tuned model in detecting diseases in tea two months after the idea's conception, and it showed a good correlation with the experts' decisions. The evaluation results showed that it is viable to perform transfer learning among domains to accelerate solutions deployments. Additionally, Edge Impulse is ideal in resource-constrained environments, especially in developing countries lacking computing resources and expertise to train DL models from scratch. This insight can propel the development and rollout of various applications addressing the Sustainable Development Goals targeted at zero hunger and no poverty, among other goals.","PeriodicalId":438536,"journal":{"name":"Proceedings of the ACM SIGCOMM Workshop on Networked Sensing Systems for a Sustainable Society","volume":"61 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131323134","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}

引用次数: 1

RealTimeAir

Proceedings of the ACM SIGCOMM Workshop on Networked Sensing Systems for a Sustainable Society Pub Date : 2022-08-22 DOI: 10.1145/3538393.3544933

S. Hart, Joseph Doyle

{"title":"RealTimeAir","authors":"S. Hart, Joseph Doyle","doi":"10.1145/3538393.3544933","DOIUrl":"https://doi.org/10.1145/3538393.3544933","url":null,"abstract":"Poor air quality has been responsible for millions of premature deaths. Acknowledging the critical role air quality plays in the future of their populations, governments across the world have been installing networks of fixed location air quality measurement instruments. But these monitoring stations are expensive and therefore spatially sparse, typically publishing summaries of hourly averages of pollutant measurements once per day. Data so sparse spatially and temporally offers little to inform the street user or policy maker as to what is happening at a more granular level, thus reducing the ability to avoid pollutants. This paper investigates the feasibility of using consumer grade mobile sensors as a means to contribute to a real time federated hyper-local crowd sensing air quality data service, RealTimeAir (RTA), underpinned by government reference sensors. We compare two mobile sensors and examine the correlation of the measurements between them. We investigate the correlation between these sensors and the more expensive fixed monitoring stations. We consider the variation of measurements over time and space to investigate the need for greater granularity of these measurements. Finally, we present a low pollutant exposure route finder as a use case for the proposed system.","PeriodicalId":438536,"journal":{"name":"Proceedings of the ACM SIGCOMM Workshop on Networked Sensing Systems for a Sustainable Society","volume":"83 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124599132","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}

引用次数: 0

A preliminary analysis of data collection and retrieval scheme for green information-centric wireless sensor networks 绿色信息中心无线传感器网络数据采集与检索方案的初步分析

Proceedings of the ACM SIGCOMM Workshop on Networked Sensing Systems for a Sustainable Society Pub Date : 2022-08-22 DOI: 10.1145/3538393.3544932

Shintaro Mori

引用次数: 1

Saving energy on smartphones through edge computing: an experimental evaluation 通过边缘计算在智能手机上节约能源:一项实验评估

Proceedings of the ACM SIGCOMM Workshop on Networked Sensing Systems for a Sustainable Society Pub Date : 2022-08-22 DOI: 10.1145/3538393.3544935

Chiara Caiazza, Valerio Luconi, Alessio Vecchio

引用次数: 0

A renewable energy-aware distributed task scheduler for multi-sensor IoT networks 面向多传感器物联网网络的可再生能源感知分布式任务调度程序

Proceedings of the ACM SIGCOMM Workshop on Networked Sensing Systems for a Sustainable Society Pub Date : 2022-08-22 DOI: 10.1145/3538393.3544936

Elizabeth Liri, K. Ramakrishnan, K. Kar

引用次数: 1