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INDONESIA
Indonesian Journal of Electrical Engineering and Computer Science
Published by Institute of Advanced Engineering and Science
ISSN : 25024752     EISSN : 25024760     DOI : -
Core Subject :
Arjuna Subject : -
Articles 65 Documents
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Search results for , issue "Vol 38, No 3: June 2025" : 65 Documents clear
Internet of things based autonomous robot system architecture for home automation and healthcare services Karuna Sagar, Bhimunipadu Jestadi Job; Latha, Garapati Swarna; Bolla, Sreenivasulu; Nanajkar, Jyotsna Amit; Patnala, Pattabhirama Mohan; Mande, Praveen; Kharde, Mukund Ramdas; Narasimharao, Jonnadula
Indonesian Journal of Electrical Engineering and Computer Science Vol 38, No 3: June 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v38.i3.pp1624-1633

Abstract

The internet of things (IoT) is playing a major role in the development of the health industry by enabling more accessible and affordable virtual and distant patient contacts through applications that are easy to use. The IoT and automated homes are becoming more popular in recent days. A network of connected devices, including hardware, equipment, and technical support, is known as the IoT. Their purpose is to allow data exchange with other systems through the internet. This paper presents, internet of things based autonomous robot system architecture (IoT-ARSA) for home automation and healthcare services. The primary goal of this secure home automation system is to help the elderly and disabled people by allowing them to operate home appliances. Additionally, the system uses a cloud server to predict the health conditions of patients and the elderly people, providing information to a guardian. The patient's health condition is determined using sensors like temperature, pulse, blood pressure, and oxygen level. Ultrasonic sensor and face detection are used for home automation. Each sensor will interact with the Raspberry Pi 4 to record data, which will then be processed and stored in the cloud. From results it is clear that described (IoT-ARSA) for home automation and healthcare services model is very efficient with high accuracy and high security. Health monitoring is achieved with this model continuously with great efficiency.
Long-term user engagement in recommender systems: a review Edem, Swathi; Naresh Yadav, B. V. Ram
Indonesian Journal of Electrical Engineering and Computer Science Vol 38, No 3: June 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v38.i3.pp2050-2058

Abstract

The purpose of recommender systems (RS) is to facilitate user collaboration and communication on the platform. Nevertheless, there is limited knowledge regarding the extent of this relationship and the techniques by which RS could promote persistent user engagement with the platform. In order to fill this void, the present study investigates the role of RS in transforming users’ short-term engagement with the RS into long-lasting involvement with the platform. We present a theoretical framework by reviewing relevant literature in the domains of RS and user engagement to probe these issues. We provide open challenges in this field along with metrics in the present study.
The variety of phosphor Ca2MgSi2O7:Eu2+ emission color affect white light LEDs Van De, Pham; Nguyen Thi, My Hanh
Indonesian Journal of Electrical Engineering and Computer Science Vol 38, No 3: June 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v38.i3.pp1471-1478

Abstract

The conventional phosphor-converted white light emitting diode (WLED) suffers from several drawbacks relevant to heat generation and low rendered performance. Thus, using ultraviolet LEDs was introduced as a solution. It is essential to choose the phosphors with high stability that can activated under 350-410 nm to be compatible with the chips. Rare-earth-doped silicate phosphor is among the most reserched materials for solid-state light devices, thanks to its high stability and low-cost production. This work presents the Eu2+ -doped Ca2MgSi2O7 green phosphor to serve the pursuit of comprehensively enhancing the WLED performances. The f–d transitions and Eu2+ ions mixture take possession of two seperate cation spots in main grids with the help of two emission peaks, one at 465 nm and another at 520 nm. The composition of YAG:Ce3+ and Ca2MgSi2O7:Eu2+ phosphors, and a near-UV chip of 370 nm were utilized to compose WLEDs. Results show that by increasing the Ca2MgSi2O7:Eu2+ phosphor amount, the lumen output, correlated color homogeneity, and color rendering factors can be improved. The paper emphasizes the necessity for the optimal selection of the Ca2MgSi2O7:Eu2+ phosphor concentration, which would be about 10 wt%. The phosphors could be promising in making green-induced white luminous materials for white pc-LEDs with near UV-base.
ClearNet: auto-encoder based denoising model for endoscopy images Shokeen, Vikrant; Kumar, Sandeep; Mathur, Vidhu; Sharma, Amit; Gupta, Indrajeet; Jain, Parita
Indonesian Journal of Electrical Engineering and Computer Science Vol 38, No 3: June 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v38.i3.pp1990-2000

Abstract

Gastrointestinal (GI) endoscopy images play a crucial role in the detection and diagnosis of diseases within the digestive tract. However, the development of effective computer vision models for automated analysis and denoising of endoscopy images faces challenges arising from the diverse nature of abnormalities and the presence of image artefacts. In this work, the utilization of an encoder-decoder network for denoising GI endoscopy images using the HyperKvasir dataset has been analyzed. This approach involves training a custom encoder-decoder model on this extensive multiclass endoscopy image dataset and assessing its performance across 23 prevalent classes of digestive tract issues. Here experiments showcase the model’s ability to learn robust visual representations from endoscopic data, enabling accurate disease prediction. The achieved promising results highlight the potential of encoder-decoder architectures as a foundational framework for computer-aided endoscopy analysis with a specific focus on denoising applications. Our model manages to increase the peak signal-tonoise ratio (PSNR) of original-noisy pair from 19.118954 to 69.892631 for original-reconstructed pair showcasing almost perfect reconstruction.
Deep learning-based secured resilient architecture for IoT-driven critical infrastructure Vaddadi, Srinivas A.; Vallabhaneni, Rohith; Somanathan Pillai, Sanjaikanth E. Vadakkethil; Addula, Santosh Reddy; Ananthan, Bhuvanesh
Indonesian Journal of Electrical Engineering and Computer Science Vol 38, No 3: June 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v38.i3.pp1819-1829

Abstract

While enabling remote management and efficiency improvements, the infrastructure of the smart city becomes able to advance due to the consequences of the internet of things (IoT). The development of IoT in the fields of agriculture, robotics, transportation, computerization, and manufacturing. Based on the serious infrastructure environments, smart revolutions and digital transformation play an important role. According to various perspectives on issues of privacy and security, the challenge is heterogeneous data handling from various devices of IoT. The critical IoT infrastructure with its regular operations is jeopardized by the sensor communication among both IoT devices depending upon the attacker targets. This research suggested a novel deep belief network (DBN) and a secured data dissemination structure based on blockchain to address the issues of privacy and security infrastructures. The non-local means filter performs pre-processing and the feature selection is achieved using the improved crystal structure (ICS) algorithm. The DBN model for the classification of attack and non-attack data. For the non-attacked data, the security is offered via a blockchain network incorporated with the interplanetary file system.

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