2018 IEEE Green Technologies Conference (GreenTech)最新文献_第2页

Development of Smart Interior Environmental Mobile App for Health Monitoring 健康监测智能室内环境移动应用开发

2018 IEEE Green Technologies Conference (GreenTech) Pub Date : 2018-04-04 DOI: 10.1109/GREENTECH.2018.00029

Rosemarie J. Day, Hassan S. Salehi

{"title":"Development of Smart Interior Environmental Mobile App for Health Monitoring","authors":"Rosemarie J. Day, Hassan S. Salehi","doi":"10.1109/GREENTECH.2018.00029","DOIUrl":"https://doi.org/10.1109/GREENTECH.2018.00029","url":null,"abstract":"Migraines are the sixth most disabling disease in the world, affecting more than 1 billion people worldwide and are just one illness affected by environmental triggers due to changes to that occur inside the home. Due to migraines similarities to sinus headaches, migraines affected by environmental triggers can often be misdiagnosed. The development of a smart interior environmental mobile app for health monitoring is designed to take in environmental data from a user's surroundings, i.e. temperature, humidity, pressure and altitude, while also taking in user data about their chronic illnesses affected by environmental changes. These two datasets are then combined and utilized to define a user's common environment and chronic illness attacks. Once the data has been collected, an iOS app analyzes the illness in terms of the changes going on in the environment, looking for correlations that exist, common trigger points and areas of concern in the user's home environment, such as temperature, humidity, etc. This device is targeted at those who suffer from migraine attacks and believe that there is some environmental factor contributing to their migraines. This paper discusses an Internet of Things (IoT) health monitoring analyzer design used to aide user's suffering from migraines and recognize trigger areas in their environment to assist in living a healthier lifestyle.","PeriodicalId":387970,"journal":{"name":"2018 IEEE Green Technologies Conference (GreenTech)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121261274","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: 5

On the Stability of DC Microgrids with Two Constant Power Devices 双恒功率装置直流微电网稳定性研究

2018 IEEE Green Technologies Conference (GreenTech) Pub Date : 2018-04-04 DOI: 10.1109/GREENTECH.2018.00015

A. Garcés, Alexander Gutiérrez

引用次数: 5

Empirical Modeling of Acoustic Signal Attenuation in Municipal Sewer Pipes for Condition Monitoring Applications 用于状态监测的城市下水管道声信号衰减的经验建模

2018 IEEE Green Technologies Conference (GreenTech) Pub Date : 2018-04-01 DOI: 10.1109/GREENTECH.2018.00033

M. Khan

{"title":"Empirical Modeling of Acoustic Signal Attenuation in Municipal Sewer Pipes for Condition Monitoring Applications","authors":"M. Khan","doi":"10.1109/GREENTECH.2018.00033","DOIUrl":"https://doi.org/10.1109/GREENTECH.2018.00033","url":null,"abstract":"An important challenge for a smart city is to prevent occurrence of sewer system overflows (SSOs) that can degrade the environment and pose a public health hazard. To prevent SSOs, timely detection and cleaning of clogged sewer pipes is essential. Present industry standard to detect sewer blockage is based on passing a close circuit television (CCTV) mounted crawler through the pipes. An operator observes the video and annotates it based on the condition of a pipe. This system is complex, expensive and man-hour intensive. There is a need to develop an acoustic based method that can replace the traditional CCTV based system. Clogged pipes cause severe attenuation on acoustic signals which can be used as a measure of existence and extent of blockage. This study reports an empirical based approach to determine acoustic signal attenuation in sewer pipes. Extensive field measurements were made in Charlotte, North Carolina to collect in-pipe signal propagation data from installed sewers to support this work. The findings were used to justify further research and development by a technology startup company that successfully produced an acoustic based sewer line blockage detection system.","PeriodicalId":387970,"journal":{"name":"2018 IEEE Green Technologies Conference (GreenTech)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126105871","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: 4

Analysis of Grid Connected Fuel Cell Power System Integrated with Supercapacitor 集成超级电容器的并网燃料电池动力系统分析

2018 IEEE Green Technologies Conference (GreenTech) Pub Date : 2018-04-01 DOI: 10.1109/GREENTECH.2018.00020

Nimat Shamim, A. Bilbao, D. Reale, S. Bayne

引用次数: 5

Toward a Sensor Trustworthiness Measure for Grid-Connected IoT-Enabled Smart Cities 面向并网物联网智能城市的传感器可信度测度

2018 IEEE Green Technologies Conference (GreenTech) Pub Date : 2018-04-01 DOI: 10.1109/GREENTECH.2018.00038

Megan Culler, K. Davis

引用次数: 4

IoT Security: ZWave and Thread 物联网安全:ZWave和线程

2018 IEEE Green Technologies Conference (GreenTech) Pub Date : 2018-04-01 DOI: 10.1109/GREENTECH.2018.00040

Ishaq Unwala, Z. Taqvi, Jiang Lu

引用次数: 23

Flexibility Measurement of Power System Generation for Real-Time Applications Using Analytical Hierarchy Process 基于层次分析法的电力系统发电灵活性实时测量

2018 IEEE Green Technologies Conference (GreenTech) Pub Date : 2018-04-01 DOI: 10.1109/GREENTECH.2018.00011

A. A. Shetaya, R. El-Azab, A. Amin, Omar H. Abdalla

{"title":"Flexibility Measurement of Power System Generation for Real-Time Applications Using Analytical Hierarchy Process","authors":"A. A. Shetaya, R. El-Azab, A. Amin, Omar H. Abdalla","doi":"10.1109/GREENTECH.2018.00011","DOIUrl":"https://doi.org/10.1109/GREENTECH.2018.00011","url":null,"abstract":"The purpose of this paper is to introduce a new technique to measure the flexibility of power system generation in real-time. The proposed technique uses the analytical hierarchy process to evaluate the flexibility by combining the essential power sources features. The flexibility features of minimum power, ramp-rate capability, start-up time and the controllability are expressed as a single indexed time-series. Effective flexibility measurement techniques are required because of the recent increasing penetration of variable renewable energy resources in the power systems. The proposed flexibility index copes with the complexity and difficulty of the high variability power sources by taking the index into account in the power dispatching process. Simulation studies are conducted to validate the effectiveness of the new flexibility measurement technique. The results show the success of the flexibility measurement index to represent the real value of the flexibility of each power source and also, the overall system flexibility. The measurements help the power system operators to take the right dispatching decision during the optimal set-points calculations of all sources in the electric power grid.","PeriodicalId":387970,"journal":{"name":"2018 IEEE Green Technologies Conference (GreenTech)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133631421","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: 7

Scheduling of Community Based Charging Stations with Genetic Algorithms 基于遗传算法的社区充电站调度

2018 IEEE Green Technologies Conference (GreenTech) Pub Date : 2018-04-01 DOI: 10.1109/GREENTECH.2018.00023

G. Koutitas

引用次数: 2

Data-Driven Topology Estimation with Limited Sensors in Radial Distribution Feeders 径向馈线中有限传感器的数据驱动拓扑估计

2018 IEEE Green Technologies Conference (GreenTech) Pub Date : 2018-04-01 DOI: 10.1109/GREENTECH.2018.00041

M. Bariya, A. von Meier, A. Ostfeld, E. Ratnam

引用次数: 5

Modeling the Determinants of Residential Appliance Electricity Use Single-Family Homes, Homes with Electric Vehicles and Apartments 单户住宅、电动汽车住宅和公寓的家用电器用电决定因素建模

2018 IEEE Green Technologies Conference (GreenTech) Pub Date : 2018-04-01 DOI: 10.1109/GREENTECH.2018.00030

M. Jafary, L. Shephard

{"title":"Modeling the Determinants of Residential Appliance Electricity Use Single-Family Homes, Homes with Electric Vehicles and Apartments","authors":"M. Jafary, L. Shephard","doi":"10.1109/GREENTECH.2018.00030","DOIUrl":"https://doi.org/10.1109/GREENTECH.2018.00030","url":null,"abstract":"This study provides a data mining-based methodology for setting decision-making rules to identify determinants of appliance electricity consumption based on four years of data from 800 single-family homes and apartments in Austin, Texas. These data were collected from single-family homes (i.e., reference case), single-family homes that owned electric vehicles (EV) and apartments containing multiple families. Cluster analysis was performed to group homes based on their calculated average hourly appliance electricity use, resident building attributes, and socioeconomic characteristics of building residents. Results of regression analysis indicate that variables from all three building types are significantly correlated to appliance electricity consumption. Residents of reference homes and single-family homes with EV tend to spend more time at homes, resulting in higher appliance consumption. Residents that own EVs generally attain a higher education level but do not necessarily having a lower consumption of appliances. Residents with higher income tend to have higher electricity consumption. The results of the analysis can provide new insights and tools for policymakers governing community development and for the utility sector as they seek to deploy new programs to optimize electricity use with existing generation capacity and enhance customer service in response to the growing demand for distributed generation in communities across America.","PeriodicalId":387970,"journal":{"name":"2018 IEEE Green Technologies Conference (GreenTech)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116520785","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: 5