Pub Date : 2020-10-28DOI: 10.1109/UEMCON51285.2020.9298051
Lama A. Alqahtani, Hanadi M. Alotaibi, Irfan Ullah Khan, N. Aslam
Nowadays, heart disease is considered as one of the most significant factors of death. Several attempts have been made over the last few years to automate the diagnosis of cardiac disease. Nevertheless, the significance of machine learning has already been proved from literature studies. In our study, several machine learning algorithms such as Naive Bayes (NB), Multi-Layer Perceptron (MLP), Random Forest (RF) and Decision Tree (DT) will be compared to predict presence of heart disease using UCI data set. Several preprocessing techniques will be applied; brute force technique will be used for feature selection. Grid search mechanism will be used for parameter optimization. Experiments showed that Random Forest achieved the highest performance with the accuracy of 0.93 and AUC of 0.95.
{"title":"Automated prediction of Heart disease using optimized machine learning techniques","authors":"Lama A. Alqahtani, Hanadi M. Alotaibi, Irfan Ullah Khan, N. Aslam","doi":"10.1109/UEMCON51285.2020.9298051","DOIUrl":"https://doi.org/10.1109/UEMCON51285.2020.9298051","url":null,"abstract":"Nowadays, heart disease is considered as one of the most significant factors of death. Several attempts have been made over the last few years to automate the diagnosis of cardiac disease. Nevertheless, the significance of machine learning has already been proved from literature studies. In our study, several machine learning algorithms such as Naive Bayes (NB), Multi-Layer Perceptron (MLP), Random Forest (RF) and Decision Tree (DT) will be compared to predict presence of heart disease using UCI data set. Several preprocessing techniques will be applied; brute force technique will be used for feature selection. Grid search mechanism will be used for parameter optimization. Experiments showed that Random Forest achieved the highest performance with the accuracy of 0.93 and AUC of 0.95.","PeriodicalId":433609,"journal":{"name":"2020 11th IEEE Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON)","volume":"214 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121623890","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 : 2020-10-28DOI: 10.1109/UEMCON51285.2020.9298142
Stelios N. Neophytou, Pavlos Tsiantis, Ilias Alexopoulos, I. Kyriakides, Camille de Veyrac, Ehson Abdi, D. Hayes
The maritime environment is characterized by a scarcity of resources of power, sensing, processing, and communications. The resource constraints impose limitations in information acquisition which involves data collection and data processing to yield meaningful statistics. The contribution of this work is on custom software and hardware methods for low power, low data-rate processing for the application of classification of ocean sounds. The combination of light processing software and custom hardware allow the development of efficient cyber-physical maritime IoT systems. A simulation-based study is provided to evaluate the ability of the software method for agile learning of features for ocean sounds classification. In addition, a practical implementation on a custom hardware emulator is provided to demonstrate the potential of the method to classify ocean sounds on low power, inexpensive seaborne IoT nodes.
{"title":"Agile Edge Classification of Ocean Sounds","authors":"Stelios N. Neophytou, Pavlos Tsiantis, Ilias Alexopoulos, I. Kyriakides, Camille de Veyrac, Ehson Abdi, D. Hayes","doi":"10.1109/UEMCON51285.2020.9298142","DOIUrl":"https://doi.org/10.1109/UEMCON51285.2020.9298142","url":null,"abstract":"The maritime environment is characterized by a scarcity of resources of power, sensing, processing, and communications. The resource constraints impose limitations in information acquisition which involves data collection and data processing to yield meaningful statistics. The contribution of this work is on custom software and hardware methods for low power, low data-rate processing for the application of classification of ocean sounds. The combination of light processing software and custom hardware allow the development of efficient cyber-physical maritime IoT systems. A simulation-based study is provided to evaluate the ability of the software method for agile learning of features for ocean sounds classification. In addition, a practical implementation on a custom hardware emulator is provided to demonstrate the potential of the method to classify ocean sounds on low power, inexpensive seaborne IoT nodes.","PeriodicalId":433609,"journal":{"name":"2020 11th IEEE Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON)","volume":"126 9","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114009279","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 : 2020-10-28DOI: 10.1109/UEMCON51285.2020.9298046
A. Asadoorian, Melvin Alberto, M. Ali
In this paper, we outline the Software Development LifeCycle (SDLC: requirements elicitation & definition, design, implementation, testing, and maintenance) and seek to find and convey the best practices for security throughout the it. Security should be made a priority when defining system requirements; system design and architecture should embody those requirements through secure models (supporting integrity, confidentiality, authorization); developers should translate those specifications to the code; proper test cases should be devised in order to assess possible vulnerabilities of completed systems; maintenance and evolution teams should be cognizant of previous security measures to avoid compromising them with functional improvements. Further, there are measures that should be taken outside of and after the completion of this cycle to reduce the risk of successful attacks both in terms of securing data and in terms of compounding the difficulty of reverse engineering. Methods include new approaches to authentication, the old standby of cryptography, and obfuscating source code so that exploiting it will be difficult. Employing all of these strategies in tandem should produce secure yet functional systems with security present in all layers; the more barriers that stand in an attacker’s way, the less often an attack will be attempted and those increases the reactionary time that system administrators have to respond to attacks in progress.
{"title":"Creating and Using Secure Software","authors":"A. Asadoorian, Melvin Alberto, M. Ali","doi":"10.1109/UEMCON51285.2020.9298046","DOIUrl":"https://doi.org/10.1109/UEMCON51285.2020.9298046","url":null,"abstract":"In this paper, we outline the Software Development LifeCycle (SDLC: requirements elicitation & definition, design, implementation, testing, and maintenance) and seek to find and convey the best practices for security throughout the it. Security should be made a priority when defining system requirements; system design and architecture should embody those requirements through secure models (supporting integrity, confidentiality, authorization); developers should translate those specifications to the code; proper test cases should be devised in order to assess possible vulnerabilities of completed systems; maintenance and evolution teams should be cognizant of previous security measures to avoid compromising them with functional improvements. Further, there are measures that should be taken outside of and after the completion of this cycle to reduce the risk of successful attacks both in terms of securing data and in terms of compounding the difficulty of reverse engineering. Methods include new approaches to authentication, the old standby of cryptography, and obfuscating source code so that exploiting it will be difficult. Employing all of these strategies in tandem should produce secure yet functional systems with security present in all layers; the more barriers that stand in an attacker’s way, the less often an attack will be attempted and those increases the reactionary time that system administrators have to respond to attacks in progress.","PeriodicalId":433609,"journal":{"name":"2020 11th IEEE Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON)","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124308767","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 : 2020-10-28DOI: 10.1109/UEMCON51285.2020.9298056
S. Chawathe
An estimate of the number of items in a database that satisfy an equality or range predicate is useful for several tasks, such as cost-based query optimization, provisioning of system resources, and determining the financial costs of using database services. In a traditional database system, such estimates are computed and used internally by the system and have been well studied. In contrast, such estimates have not received much attention in the context of a cloud-based database service, where they must be computed by the application that uses the service using only the limited features of the interface provided by the service. This paper motivates and formulates the selectivity-estimation problem for database services. It describes the characteristics of this problem that distinguish it from the analogous problem in traditional database systems. It outlines some subproblems and methods to address them. It provides a method for estimating selectivities based on random sampling along with some experimental results.
{"title":"Estimating Predicate Selectivities in a NoSQL Database Service","authors":"S. Chawathe","doi":"10.1109/UEMCON51285.2020.9298056","DOIUrl":"https://doi.org/10.1109/UEMCON51285.2020.9298056","url":null,"abstract":"An estimate of the number of items in a database that satisfy an equality or range predicate is useful for several tasks, such as cost-based query optimization, provisioning of system resources, and determining the financial costs of using database services. In a traditional database system, such estimates are computed and used internally by the system and have been well studied. In contrast, such estimates have not received much attention in the context of a cloud-based database service, where they must be computed by the application that uses the service using only the limited features of the interface provided by the service. This paper motivates and formulates the selectivity-estimation problem for database services. It describes the characteristics of this problem that distinguish it from the analogous problem in traditional database systems. It outlines some subproblems and methods to address them. It provides a method for estimating selectivities based on random sampling along with some experimental results.","PeriodicalId":433609,"journal":{"name":"2020 11th IEEE Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127740996","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 : 2020-10-28DOI: 10.1109/UEMCON51285.2020.9298183
Narayana Darapaneni, Amol Kobal, Rohit Chaoji, R. Tiwari, S. Saurav, A. Paduri
The Coronavirus (or Covid-19) outbreak is a major global pandemic, which has infected millions of people across the world. India has been one of the worst hit country by this pandemic with over 4.5 million people affected by the virus as of 10th Sept 2020. The governments in India took various methods to contain the outbreak including non-medical interventions like lockdown. This document provides detailed analysis of effect of lockdown in containing the spread of Covid-19 in India. This work comprises of applying different statistical techniques to comprehend the Virus progression during various phases of lockdown implemented across India.
{"title":"Effects of Lockdown and Post Lockdown on Covid19 cases across India using Supervised Learning Techniques","authors":"Narayana Darapaneni, Amol Kobal, Rohit Chaoji, R. Tiwari, S. Saurav, A. Paduri","doi":"10.1109/UEMCON51285.2020.9298183","DOIUrl":"https://doi.org/10.1109/UEMCON51285.2020.9298183","url":null,"abstract":"The Coronavirus (or Covid-19) outbreak is a major global pandemic, which has infected millions of people across the world. India has been one of the worst hit country by this pandemic with over 4.5 million people affected by the virus as of 10th Sept 2020. The governments in India took various methods to contain the outbreak including non-medical interventions like lockdown. This document provides detailed analysis of effect of lockdown in containing the spread of Covid-19 in India. This work comprises of applying different statistical techniques to comprehend the Virus progression during various phases of lockdown implemented across India.","PeriodicalId":433609,"journal":{"name":"2020 11th IEEE Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126409535","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 : 2020-10-28DOI: 10.1109/UEMCON51285.2020.9298148
Golam Kayas, J. Payton, M. Hossain, S. Islam
The ubiquitous nature of IoT devices has brought new and exciting applications in computing and communication paradigms. Due to its ability to enable auto-configurable communication between IoT devices, pervasive applications, and remote clients, the use of the Universal Plug and Play (UPnP) protocol is widespread. However, the advertisement and discovery mechanism of UPnP incurs significant overhead on resource-constrained IoT devices. In this paper, we propose a delegation-based approach that extends the UPnP protocol by offloading the service advertisement and discovery-related overhead from resource-limited IoT devices to the resource-rich neighbours of a UPnP-enabled IoT network. Our experimental evaluations demonstrate that the proposed scheme shows significant improvement over the basic UPnP, reducing energy consumption and network overhead.
{"title":"VSDM: A Virtual Service Device Management Scheme for UPnP-Based IoT Networks","authors":"Golam Kayas, J. Payton, M. Hossain, S. Islam","doi":"10.1109/UEMCON51285.2020.9298148","DOIUrl":"https://doi.org/10.1109/UEMCON51285.2020.9298148","url":null,"abstract":"The ubiquitous nature of IoT devices has brought new and exciting applications in computing and communication paradigms. Due to its ability to enable auto-configurable communication between IoT devices, pervasive applications, and remote clients, the use of the Universal Plug and Play (UPnP) protocol is widespread. However, the advertisement and discovery mechanism of UPnP incurs significant overhead on resource-constrained IoT devices. In this paper, we propose a delegation-based approach that extends the UPnP protocol by offloading the service advertisement and discovery-related overhead from resource-limited IoT devices to the resource-rich neighbours of a UPnP-enabled IoT network. Our experimental evaluations demonstrate that the proposed scheme shows significant improvement over the basic UPnP, reducing energy consumption and network overhead.","PeriodicalId":433609,"journal":{"name":"2020 11th IEEE Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON)","volume":"137 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125429061","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 : 2020-10-28DOI: 10.1109/UEMCON51285.2020.9298086
S. Chawathe
Online auctions as exemplified by sites such as ebay.com are responsible for very large volumes of transactions and monetary value. Their growth has also led to a growth in fraudulent activities in these markets. This paper studies transaction data from such auctions with the goal of using it to detect anomalous and potentially fraudulent bidding. To that end, it explores several approaches based on classification, clustering, and visualization. The quantitative results signal very high accuracy in classification but their promise is tempered by some limitations of the experimental dataset. Clustering and visualizations using self-organizing maps (SOMs) is found to be more effective for this data than clustering using more conventional methods such as k-means. In particular, the SOMs reveal several interesting relationships among the dataset’s attributes and their correlations to anomalous bidding.
{"title":"Analyzing Auction Data for Anomalous Bidding","authors":"S. Chawathe","doi":"10.1109/UEMCON51285.2020.9298086","DOIUrl":"https://doi.org/10.1109/UEMCON51285.2020.9298086","url":null,"abstract":"Online auctions as exemplified by sites such as ebay.com are responsible for very large volumes of transactions and monetary value. Their growth has also led to a growth in fraudulent activities in these markets. This paper studies transaction data from such auctions with the goal of using it to detect anomalous and potentially fraudulent bidding. To that end, it explores several approaches based on classification, clustering, and visualization. The quantitative results signal very high accuracy in classification but their promise is tempered by some limitations of the experimental dataset. Clustering and visualizations using self-organizing maps (SOMs) is found to be more effective for this data than clustering using more conventional methods such as k-means. In particular, the SOMs reveal several interesting relationships among the dataset’s attributes and their correlations to anomalous bidding.","PeriodicalId":433609,"journal":{"name":"2020 11th IEEE Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122270939","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 : 2020-10-28DOI: 10.1109/UEMCON51285.2020.9298075
Baker Al Smadi, Manki Min
Credit card fraud is one of the most important threats that affect people as well as companies across the world, particularly with the growing volume of financial transactions using credit cards every day. This puts the security of financial transactions at serious risk and calls for a fundamental solution. In this paper, we discuss various techniques of credit card fraud detection techniques that provide enhanced protection for credit card systems against a variety of frauds. We also compare these techniques in terms of accuracy, time, and cost, and outlined potential strengths and weaknesses to provide a guideline to choose the right technique.
{"title":"A Critical review of Credit Card Fraud Detection Techniques","authors":"Baker Al Smadi, Manki Min","doi":"10.1109/UEMCON51285.2020.9298075","DOIUrl":"https://doi.org/10.1109/UEMCON51285.2020.9298075","url":null,"abstract":"Credit card fraud is one of the most important threats that affect people as well as companies across the world, particularly with the growing volume of financial transactions using credit cards every day. This puts the security of financial transactions at serious risk and calls for a fundamental solution. In this paper, we discuss various techniques of credit card fraud detection techniques that provide enhanced protection for credit card systems against a variety of frauds. We also compare these techniques in terms of accuracy, time, and cost, and outlined potential strengths and weaknesses to provide a guideline to choose the right technique.","PeriodicalId":433609,"journal":{"name":"2020 11th IEEE Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134212096","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 : 2020-10-28DOI: 10.1109/UEMCON51285.2020.9298117
Sinead V. Fernandes, M. S. Ullah
This paper presents the test results of analyzing mel frequency cepstrum coefficient (MFCC), delta and difference cepstrum features to detect and distinguish the truthful and deceptive speech. The features are extracted based on the psychoacoustic masking property of human speech and how it is perceived. Truthful and deceptive speeches are preset based off a guilty male speaker in police custody. Delta cepstrum and time-difference cepstrum features at triangular critical bands filter and a neural network show the distinctions that determine whether an utterance is truthful or deceptive. In this paper, we analyze the extracted MFCC, delta cepstrum and time-difference cepstrum features to see how stress in speech accurately conveys human speech emotion and deception. Finally, we feed the data into an artificial neural network model to test out the results.
{"title":"Phychoacoustic Masking of Delta and Time -Difference Cepstrum Features for Deception Detection","authors":"Sinead V. Fernandes, M. S. Ullah","doi":"10.1109/UEMCON51285.2020.9298117","DOIUrl":"https://doi.org/10.1109/UEMCON51285.2020.9298117","url":null,"abstract":"This paper presents the test results of analyzing mel frequency cepstrum coefficient (MFCC), delta and difference cepstrum features to detect and distinguish the truthful and deceptive speech. The features are extracted based on the psychoacoustic masking property of human speech and how it is perceived. Truthful and deceptive speeches are preset based off a guilty male speaker in police custody. Delta cepstrum and time-difference cepstrum features at triangular critical bands filter and a neural network show the distinctions that determine whether an utterance is truthful or deceptive. In this paper, we analyze the extracted MFCC, delta cepstrum and time-difference cepstrum features to see how stress in speech accurately conveys human speech emotion and deception. Finally, we feed the data into an artificial neural network model to test out the results.","PeriodicalId":433609,"journal":{"name":"2020 11th IEEE Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134520551","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 : 2020-10-28DOI: 10.1109/UEMCON51285.2020.9298164
Jeremy Lytle, D. Santillo, K. Mai, Jeremy Wright
Green roofs are rapidly becoming ubiquitous tools for stormwater management in the urban setting for their ability to divert water from centralized treatment plants and support natural water cycles. In doing so, the performance of a green roof system is dependent on the process of evapotranspiration, which is a function of microclimatic conditions. The work herein presents a remote monitoring architecture for measurement of evapotranspiration performance from a variety of different green roof topologies in an urban setting. The data acquisition system employs an i2c bus to coordinate an array of loads cells, controlled by a central microcomputer which is WIFI connected and cloud interactive. Resulting datasets will contribute to the refinement of agricultural evapotranspiration models towards green roof applications, as well as the characterization of design and microclimate related performance impacts. Preliminary results indicate reliable functionality and data quality from the remote monitoring system. This outcome supports the value of active instrumentation and performance monitoring to the advancement of green roof technology. Going forward, post-processing methods will be expanded, and the system will be applied to additional green roof topologies for the 2021 growing season.
{"title":"Remote monitoring of evapotranspiration from green roof systems","authors":"Jeremy Lytle, D. Santillo, K. Mai, Jeremy Wright","doi":"10.1109/UEMCON51285.2020.9298164","DOIUrl":"https://doi.org/10.1109/UEMCON51285.2020.9298164","url":null,"abstract":"Green roofs are rapidly becoming ubiquitous tools for stormwater management in the urban setting for their ability to divert water from centralized treatment plants and support natural water cycles. In doing so, the performance of a green roof system is dependent on the process of evapotranspiration, which is a function of microclimatic conditions. The work herein presents a remote monitoring architecture for measurement of evapotranspiration performance from a variety of different green roof topologies in an urban setting. The data acquisition system employs an i2c bus to coordinate an array of loads cells, controlled by a central microcomputer which is WIFI connected and cloud interactive. Resulting datasets will contribute to the refinement of agricultural evapotranspiration models towards green roof applications, as well as the characterization of design and microclimate related performance impacts. Preliminary results indicate reliable functionality and data quality from the remote monitoring system. This outcome supports the value of active instrumentation and performance monitoring to the advancement of green roof technology. Going forward, post-processing methods will be expanded, and the system will be applied to additional green roof topologies for the 2021 growing season.","PeriodicalId":433609,"journal":{"name":"2020 11th IEEE Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134575492","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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