Literature DB >> 34300671

Towards Smart Home Automation Using IoT-Enabled Edge-Computing Paradigm.

Hikmat Yar1, Ali Shariq Imran2, Zulfiqar Ahmad Khan3, Muhammad Sajjad1,2, Zenun Kastrati4.   

Abstract

Smart home applications are ubiquitous and have gained popularity due to the overwhelming use of Internet of Things (IoT)-based technology. The revolution in technologies has made homes more convenient, efficient, and even more secure. The need for advancement in smart home technology is necessary due to the scarcity of intelligent home applications that cater to several aspects of the home simultaneously, i.e., automation, security, safety, and reducing energy consumption using less bandwidth, computation, and cost. Our research work provides a solution to these problems by deploying a smart home automation system with the applications mentioned above over a resource-constrained Raspberry Pi (RPI) device. The RPI is used as a central controlling unit, which provides a cost-effective platform for interconnecting a variety of devices and various sensors in a home via the Internet. We propose a cost-effective integrated system for smart home based on IoT and Edge-Computing paradigm. The proposed system provides remote and automatic control to home appliances, ensuring security and safety. Additionally, the proposed solution uses the edge-computing paradigm to store sensitive data in a local cloud to preserve the customer's privacy. Moreover, visual and scalar sensor-generated data are processed and held over edge device (RPI) to reduce bandwidth, computation, and storage cost. In the comparison with state-of-the-art solutions, the proposed system is 5% faster in detecting motion, and 5 ms and 4 ms in switching relay on and off, respectively. It is also 6% more efficient than the existing solutions with respect to energy consumption.

Entities:  

Keywords:  cloud computing; edge computing; home automation; internet of things; raspberry pi; smart home

Year:  2021        PMID: 34300671     DOI: 10.3390/s21144932

Source DB:  PubMed          Journal:  Sensors (Basel)        ISSN: 1424-8220            Impact factor:   3.576


  5 in total

1.  An Effective Skin Cancer Classification Mechanism via Medical Vision Transformer.

Authors:  Suliman Aladhadh; Majed Alsanea; Mohammed Aloraini; Taimoor Khan; Shabana Habib; Muhammad Islam
Journal:  Sensors (Basel)       Date:  2022-05-25       Impact factor: 3.847

2.  Abnormal Activity Recognition from Surveillance Videos Using Convolutional Neural Network.

Authors:  Shabana Habib; Altaf Hussain; Waleed Albattah; Muhammad Islam; Sheroz Khan; Rehan Ullah Khan; Khalil Khan
Journal:  Sensors (Basel)       Date:  2021-12-11       Impact factor: 3.576

3.  Vision Sensor-Based Real-Time Fire Detection in Resource-Constrained IoT Environments.

Authors:  Hikmat Yar; Tanveer Hussain; Zulfiqar Ahmad Khan; Deepika Koundal; Mi Young Lee; Sung Wook Baik
Journal:  Comput Intell Neurosci       Date:  2021-12-21

4.  Towards Hybrid Energy-Efficient Power Management in Wireless Sensor Networks.

Authors:  Rym Chéour; Mohamed Wassim Jmal; Sabrine Khriji; Dhouha El Houssaini; Carlo Trigona; Mohamed Abid; Olfa Kanoun
Journal:  Sensors (Basel)       Date:  2021-12-31       Impact factor: 3.576

5.  Research on energy saving of computer rooms in Chinese colleges and universities based on IoT and edge computing technology.

Authors:  Jia Qu
Journal:  Heliyon       Date:  2022-10-05
  5 in total

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