Complex Systems Smart Home Security Studies based Big Data Analytics

2016 ◽  
Vol 10 (6) ◽  
pp. 41-52
Author(s):  
Zhao Yan
2019 ◽  
Vol 8 (2S11) ◽  
pp. 3594-3600 ◽  

Big data analytics, cloud computing & internet of things are a smart triad which have started shaping our future towards smart home, city, business, country. Internet of things is a convergence of intelligent networks, electronic devices, and cloud computing. The source of big data at different connected electronic devices is stored on cloud server for analytics. Cloud provides the readymade infrastructure, remote processing power to consumers of internet of things. Cloud computing also gives device manufacturers and service providers access to ―advanced analytics and monitoring‖, ―communication between services and devices‖, ―user privacy and security‖. This paper, presents an overview of internet of things, role of cloud computing & big data analytics towards IoT. In this paper IoT enabled automatic irrigation system is proposed that saves data over ―ThingSpeak‖ database an IoT analytics platform through ESP8266 wifi module. This paper also summarizes the application areas and discusses the challenges of IoT.


2017 ◽  
Vol 63 (4) ◽  
pp. 426-434 ◽  
Author(s):  
A.R. Al-Ali ◽  
Imran A. Zualkernan ◽  
Mohammed Rashid ◽  
Ragini Gupta ◽  
Mazin Alikarar

2021 ◽  
Vol 5 (1) ◽  
pp. 6
Author(s):  
Suriya Priya R. Asaithambi ◽  
Sitalakshmi Venkatraman ◽  
Ramanathan Venkatraman

With the advent of the Internet of Things (IoT), many different smart home technologies are commercially available. However, the adoption of such technologies is slow as many of them are not cost-effective and focus on specific functions such as energy efficiency. Recently, IoT devices and sensors have been designed to enhance the quality of personal life by having the capability to generate continuous data streams that can be used to monitor and make inferences by the user. While smart home devices connect to the home Wi-Fi network, there are still compatibility issues between devices from different manufacturers. Smart devices get even smarter when they can communicate with and control each other. The information collected by one device can be shared with others for achieving an enhanced automation of their operations. This paper proposes a non-intrusive approach of integrating and collecting data from open standard IoT devices for personalised smart home automation using big data analytics and machine learning. We demonstrate the implementation of our proposed novel technology instantiation approach for achieving non-intrusive IoT based big data analytics with a use case of a smart home environment. We employ open-source frameworks such as Apache Spark, Apache NiFi and FB-Prophet along with popular vendor tech-stacks such as Azure and DataBricks.


Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-9
Author(s):  
Wenrui Li ◽  
Menggang Li ◽  
Yiduo Mei ◽  
Ting Li ◽  
Fang Wang

With the development of science and technology, the application of big data is becoming more and more widespread, and it has gradually expanded to various fields such as economy and commerce. Since the 2008 international financial crisis, the mainstream economics has shown deficiencies to a certain extent. On the one hand, the expressions pursued by mainstream economic theories are too strict, restricting its processing capabilities. On the other hand, the linearization method ignores the diversity, complexity, and variability of changes in the economic system, which may ignore the emergence of some serious crises. Due to the increasing distance between theoretical models and practice, theoretical models cannot guide the practice and sometimes even mislead the latter. In this paper, we propose a method of dynamic feedback early warning based on big data, which uses the LPPL model to fit parameters. Finally, we used this method to analyze the case of the A-share disaster. The research results show that the method makes the early warning coefficients of dynamic and complex systems more scientific and accurate.


Author(s):  
Abul Bashar

Big-data analytics being a useful technique in the analyzing the deeper values hidden inside a huge set of data flow that are generated in our day today lives, has almost become more prominent in variety of applications such as industrial development, smart home to smart city development and security management etc., despite its high potentials the challenges incurred makes it insufficient with certain applications that include a real time monitoring, so the paper proposes the real time monitoring of the developing manufacturing industry by proffering the intelligent big data analytics and cloud computing to present with the maximum possible insights to improvise the process of the manufacturing , by retaining the product consistency, optimal throughput and increasing the productivity.


Sensors ◽  
2016 ◽  
Vol 16 (10) ◽  
pp. 1706 ◽  
Author(s):  
Hao Chen ◽  
Xiaoyun Xie ◽  
Wanneng Shu ◽  
Naixue Xiong

2016 ◽  
Vol 10 (8) ◽  
pp. 177-198 ◽  
Author(s):  
Rita Yi Man Li ◽  
Herru Ching Yu Li ◽  
Cho Kei Mak ◽  
Tony Beiqi Tang

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