Think Home: A Smart Home as Digital  Ecosystem

Solanki, Vijender Kumar; Muthusamy, Venkatesan; Katiyar, Somesh

doi:10.4236/cs.2016.78172

Cited by 11 publications

(2 citation statements)

References 22 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Figure3illustratesthearchitectureoftheproposedsystem.Theproposedarchitecture iscategorizedintotwosubsectionsasfollows: inthefrontofthebicycletochecktheobstacles,signsandalsotakeappropriate actions according to the requirement needs. The ESP32 (Solanki et al, 2016;Balakrishnaetal.,2018;Purietal.,2019;Colin&Evrard,2019;Chauhanetal., 2018)…”

Section: Proposed Methodologymentioning

confidence: 99%

Fruitful Synergy Model of Artificial Intelligence and Internet of Thing for Smart Transportation System

Puri

Kumar

et al. 2020

International Journal of Hyperconnectivity and the Internet of Things

View full text Add to dashboard Cite

In urban transportation systems, bicycle sharing systems are majorly deployed in major cities of both developed and developing countries. The recent boom of bicycle sharing system along with its upgraded technology have opened new opportunities towards urban transportation system. With the enlargement of intelligent transportation systems (ITS's), smart bicycle sharing schemes are more popular to smart cities as a green transportation mode. In this article, the Internet of Things (IoT) and artificial intelligence-based monitoring devices have been proposed for the bicycles. This system contains a harmful exhaust gas sensor, wireless module, and a GPS receiver and camera that are capable to send data with time and date stamping. In addition, sensor also integrated on the bicycle for the fall detection. An artificial neural network (ANN) and support vector machine (SVM) applied to the data collected at central server is designed to analyze the root mean square error (RMSE), and coefficient of correlation (R2). Result shows that ANN performance is better when compared to SVM.

show abstract

Section: Proposed Methodologymentioning

confidence: 99%

Fruitful Synergy Model of Artificial Intelligence and Internet of Thing for Smart Transportation System

Puri

Kumar

et al. 2020

International Journal of Hyperconnectivity and the Internet of Things

View full text Add to dashboard Cite

show abstract

“…Sustainability dimensions order of impacts for cyber physical system (smart home) [82,[86][87][88][89].…”

Section: Business Analystmentioning

confidence: 99%

A Catalogue Supporting Software Sustainability Design

2018

View full text Add to dashboard Cite

Like other communities, sustainability in and for software design is a grand research and development challenge. Current research focuses on eliciting the meanings of sustainability and on building approaches for its engineering and integration into the mainstream software development lifecycle. However, few concrete guidelines that software designers can apply effectively are available. A guideline aims to streamline the design processes according to a set of well-known research routines or sound industry practices. Such guidelines can help software developers in the elicitation of sustainability requirements and testing software against these requirements. This paper introduces a sustainability design catalogue (SSDC) comprising a series of guidelines. It aims to assist software developers and managers in eliciting sustainability requirements, and then in measuring and testing software sustainability. The catalogue is based on reviews of the current and past research on sustainability in software engineering, which are the grounds for the development of the catalogue. Four different case studies were analyzed using the Karlskrona manifesto principles on sustainability design. A pilot framework is also proposed that includes a set of sustainability goals, concepts and methods. It exemplifies how to apply and quantify sustainability.

show abstract