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Evaluation of data mining techniques and its fusion with IoT enabled smart technologies for effective prediction of available parking space

After experiencing the hard times of pandemic situations we learned that if we could have a smart system that can help us in automatic parking of the vehicles then it could be a great help to society. This idea motivated us to carry out this current work. Though, nowadays, in almost every applicatio...

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Permalink: http://skupnikatalog.nsk.hr/Record/nsk.NSK01001131269/Details
Matična publikacija: International journal of electrical and computer engineering systems (Online)
12 (2021), 4 ; str. 187-197
Glavni autori: Dahiya, Anchal (Author), Mittal, Pooja
Vrsta građe: e-članak
Jezik: eng
Predmet:
Rudarenje podataka > IoT > Pametno parkiranje > Senzori
Online pristup: https://doi.org/10.32985/ijeces.12.4.2
International journal of electrical and computer engineering systems (Online)
Hrčak
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100 1 |a Dahiya, Anchal  |4 aut  |9 HR-ZaNSK 
245 1 0 |a Evaluation of data mining techniques and its fusion with IoT enabled smart technologies for effective prediction of available parking space  |h [Elektronička građa] /  |c Anchal Dahiya, Pooja Mittal. 
300 |b Graf. prikazi. 
504 |a Bibliografija: 20 jed. 
504 |a Abstract. 
520 |a After experiencing the hard times of pandemic situations we learned that if we could have a smart system that can help us in automatic parking of the vehicles then it could be a great help to society. This idea motivated us to carry out this current work. Though, nowadays, in almost every application domain, IoT techniques are the buzzword. IoT techniques can also be used to achieve efficacy in predicting free available parking space in advance. But the biggest challenge with IoT techniques is that they generate numerous data, which makes its analysis intangible. It was realized that if IoT techniques can be fused with outperforming data mining techniques, more efficient predictions can be performed. Thus, for this purpose, the main objective of our paper is to firstly, select the most appropriate data mining technique, based on performance evaluation, and then to perform prediction of available parking space in advance by fusing it with IoT techniques. Due to the busy schedule, the drivers need to get information about free parking spaces in advance by using smart phones. With the help of this information, it will be easy for the drivers to park their vehicle in the exact location without wasting their precious time and will maintain social distancing in crowded areas too. Data mining techniques can play an important role in the prediction of available parking space, by extracting only relevant and important information when applied to the given dataset. For this purpose, a comparative analysis of five data mining techniques such as the Support Vector Machine, K- Nearest approach, Decision Tree, Random Forest, and Ensemble learning approaches are applied on PK lot data set by using Python language. For calculation of result anaconda (spyder) is used as a supportive tool. 
653 0 |a Rudarenje podataka  |a IoT  |a Pametno parkiranje  |a Senzori 
700 1 |a Mittal, Pooja  |4 aut  |9 HR-ZaNSK 
773 0 |t International journal of electrical and computer engineering systems (Online)  |x 1847-7003  |g 12 (2021), 4 ; str. 187-197  |w nsk.(HR-ZaNSK)000739692 
981 |b Be2021  |b B01/21 
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856 4 0 |u https://hrcak.srce.hr/266744  |y Hrčak 
856 4 1 |y Digitalna.nsk.hr 

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