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Convergence of Smart City With IOT and BIG Data
* 1 , 2
1  Patliputra University, India
2  J. D. Women's College, Patliputra University, India
Academic Editor: Humbert G. Díaz

Abstract:


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Abstract.
The fast growth in the population density in urban areas demands more facilities and resources. To meet the needs of city development, the use of Internet of Things (IoT) devices and the smart systems is the very quick and valuable source. However, thousands of IoT devices are interconnecting and communicating with each other over the Internet results in generating a huge amount of data, termed as Big Data. To integrate IoT services and processing Big Data in an efficient way aimed at smart city is a challenging task. Therefore, in this paper, we proposed a system for smart city development based on IoT using Big Data Analytics. We use sensors deployment including smart home sensors, vehicular networking, weather and water sensors, smart parking sensor, and surveillance objects, etc. initially a four-tier architecture is proposed, which includes 1) Bottom Tier: which is responsible for IoT sources, data generations, and collections 2) Intermediate Tier-1: That is responsible for all type of communication between sensors, relays, base stations, the internet, etc. 3) Intermediate Tier 2: it is responsible for data management and processing using Hadoop framework, and 4) Top tier: is responsible for application and usage of the data analysis and results generated. The collected data from all smart system is processed at real-time to achieve smart cities using Hadoop with Spark, VoltDB, Storm or S4. We use existing datasets by various researchers including smart homes, smart parking weather, pollution, and vehicle for analysis and testing. All the datasets are replayed to test the real-time efficiency of the system. Finally, we evaluated the system by efficiency in term of throughput and processing time.

Internet of Things,Big Data, Smart Systems, Smart City and Hadoop.

Keywords: Internet of Things ; Big Data; Smart Systems; Smart City and Hadoop
Comments on this paper
Humbert G. Díaz
Dear authors thank you for your support to the conference.
Now we closed the publication phase and launched the post-publication phase of the conference. REVIEWWWERS'08 Brainstorming Workshop is Now Open from 2023-Jan-01 to 2023-Jan-31. MOL2NET Committee, Authors, and Validated Social Media Followers Worldwide are ... Invited to Post Moderated Questions/Answers, Comments, about papers. Please kindly post your public Answers (A) to the following questions in order to promote interchange of scientific ideas. These are my Questions (Q) to you:

Q1. What is the potential of your algorithm to develop a company startup idea based on it?
Q2. Have you considered and/or are you in process of creating a similar startup company with students of your college?
Q3. What are potential bioethics and/or data protection issues, if any, of such kind of software/company regarding General Data Protection Regulation (GDPR) in Europe?

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Humbert G. Díaz
Now the conference publication phase is close but you can answer here directly as a post-publication comment.
However, in case you want to elaborate your answers in a more structured way in the form of a short communication we can upload it on your behalf to the CATCHTOHIT-03: Congress on Acad. Transl. Res. for Companies Helping to Height. Innov. & Tech., Bilbao-Cambridge, MA, USA, 2022. https://mol2net-08.sciforum.net/catchtohit-03

Ajit Singh
To process a huge amount of data, coming with very high speed using IoT, we use Hadoop ecosystem with Spark at the top layer. The existing smart systems’ datasets are used to test and evaluate the system’s efficiency using our robust algorithm. In future, we are planning to deploy the system with our students using practical smart systems to test the real world implementation and feasibility of the system prior to initiate a startup/company.
We expect more and more suggestions from the scholar's community. Currently, we are working on potential bioethics and/or data protection issues with our proposed algorithm.



 
 
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