Home automation using general purpose household electric appliances with Raspberry Pi and commercial smartphone

Ashraf, Imran; Umer, Muhammad; Majeed, Rizwan; Mehmood, Arif; Aslam, Waqar; Yasir, Muhammad Naveed; Choi, Gyu Sang

doi:10.1371/journal.pone.0238480

Cited by 15 publications

(6 citation statements)

References 23 publications

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“…The development of user control parameters through Blynk interface (see Figure 4) allows for selection and interface customization according to preference of the user and types of appliances to be controlled. Compared to the previous works [5][6][7][8][9][10][11][12], improvement was made in terms of utilizing available open-source platform, and customizable interface. The selected platform and interface are simple, and the ability to modify and add more types of appliances to be controlled allow for greater design flexibility.…”

Section: Analysis Of the System Designmentioning

confidence: 99%

“…Current research project acknowledges the small number of research projects that have implemented home automation system for mobility impaired people to control lighting appliances with the voice command detection. Previous research has been conducted by Ashraf I. et al [5] in order to build a mobile app that controls home appliances (including lighting system) for smart home application. The system used Microsoft Azure cloud database and Raspberry Pi database server to communicate between mobile apps and home apps in which the developed multiple GUI-based interface could be of use of disabled people.…”

Section: Introductionmentioning

confidence: 99%

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Appliance Control with IOT-Arduino of Voice Command Detection for Mobility Impaired People

Zainuddin

Zubir

Aminuddin

et al. 2021

Int. J. Interact. Mob. Technol.

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People with physical mobility disabilities experience limited ability to perform daily routine. Integration between home appliances and Internet of Thing (IoT) can be used to support these people. The technology allows tasks to be performed much more easily and enable access to applications and services that would be a challenge with existing digital user interfaces. However, the developed system that is commercially available is costly and equipped with highly specific interfaces which may require considerable technical competency to conduct system interfacing. The purpose of this study is to develop a low cost IOT system for voice-enabled lamp control by utilizing Google Assistant that is available in commercial Android based mobile devices, allowing user to operate lighting appliances without moving. Personal assistance using Google platform embedded with Arduino microcontroller, ESP8266-based NodeMCU development board and integrated Blynk application allow for remote monitoring capability. The system is remotely controlled from a tablet or smartphone to assist disabled people with restricted mobility, in particular those with lower limb disabilities. The system had been tested and demonstrated that the lamp control can be easily accessed by voice command that is then validated using voice pitch analyzer. Test result indicated that capability of the integrated voice control system is verified up to a maximum distance of 24.5 meter, making it a potential implementation in any customized smart home or room system for people with mobile disability.

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Section: Analysis Of the System Designmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Appliance Control with IOT-Arduino of Voice Command Detection for Mobility Impaired People

Zainuddin

Zubir

Aminuddin

et al. 2021

Int. J. Interact. Mob. Technol.

View full text Add to dashboard Cite

show abstract

“…There is reason to believe that a good management style has a close relationship with the success or failure of many large companies [1]. Jack Welch of General Electric is regarded as the world's number one CEO, and in just 20 years since he joined General Electric in 1981, he has increased General Electric's market capitalization to $450 billion, more than 30 times, and raised its ranking from tenth to second in the world [2]. His "Six Sigma" standard, globalization and e-commerce have almost redefined modern business.…”

Section: Introductionmentioning

confidence: 99%

Transmutation and Reconstruction of Enterprise Management Model Framework Based on Improved Markov Model

Xu¹

2023

Applied Mathematics and Nonlinear Sciences

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With the deepening of socialization, the requirements for enterprises are getting higher and higher, which also prompts enterprises to innovate their management models. To enable enterprises to find the correct way to reconfigure their corporate management models, a prediction method based on an improved Markov model is used to forecast the direction of corporate management model reconfiguration. In this paper, the residuals generated by fitting GM (1, 1) at each time node are considered as the expected output values of positive and negative two random states under the state probability distribution, and the squares loss function of the residuals is established as the objective function. To obtain the minimum value of the squares loss function, the gradient descent algorithm is applied to approximate the optimal values of the probability intensity and the pending coefficients of the Kolmogorov equation under the condition of the available small amount of information, and then the Markov model correction value is determined to correct the prediction results of GM (1, 1), which effectively improves the reasonableness and feasibility of the Markov model to predict the results of the enterprise management model architecture reconstruction. The results of the calculation of the data show that According to the calculation results of the data, it can be seen that the gradient descent Markov model prediction results reduce the average relative errors of the three sets of data to 0.214%, 1.582%, and 4.134%, respectively, which is better than various other prediction models. It shows that the gradient descent algorithm based on the squares error loss function under the Markov model can effectively improve the reasonableness of the transfer probability intensity, enhance the reasonableness and reference value of the prediction results, and provide a practical direction for enterprises to reconstruct and transmute their management models under the condition of small sample data.

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“…Nowadays, we are surrounded by electronics. The number of sensors, wireless systems, home appliances, or “smart” devices around us is growing each year. , Most of these devices fall under modern buzzwords, such as “Industry 4.0”, “wearable electronics”, and “Internet of Things”. However, irrespective of their names and scope, each of these technologies requires precise, fast, cheap, and reproducible implementation methods.…”

Section: Introductionmentioning

confidence: 99%

Enhanced Assembly of Ag Nanoparticles for Surface-Independent Fabrication of Conductive Patterns

Szuwarzyński

Mazur

Borkowski

et al. 2022

ACS Appl. Nano Mater.

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Polymer stamping is a reliable and cost-effective method for producing charged patterned surfaces. However, charge stability is limited, and they discharge steadily while immersed in polar solvents. Here, we applied polyelectrolytes as the stamping medium to increase this stability. Charged line patterns were fabricated by pressing a polydimethylsiloxane (PDMS) stamp covered with a polyethylenimine (PEI) solution against silicon, glass, or polystyrene. Then, the substrate was immersed in a solution of oppositely charged silver nanoparticles. Finally, silver crystallization on the deposited nanoparticle agglomerates was performed to homogenize the conductive surface. Fabricated structures were characterized by conductive AFM, SEM, and electrical measurements. Simulations of the electric field above the pattern and electrostatic deposition of nanoparticles were performed. The presented method allows for the production of high-resolution microstructures composed of parallel 45 mm paths with a width of 10 μm and a thickness below 100 nm. A conductivity of 104 S/m is high enough to keep a commercial LED on.

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Home automation using general purpose household electric appliances with Raspberry Pi and commercial smartphone

Cited by 15 publications

References 23 publications

Appliance Control with IOT-Arduino of Voice Command Detection for Mobility Impaired People

Appliance Control with IOT-Arduino of Voice Command Detection for Mobility Impaired People

Transmutation and Reconstruction of Enterprise Management Model Framework Based on Improved Markov Model

Enhanced Assembly of Ag Nanoparticles for Surface-Independent Fabrication of Conductive Patterns

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