| Journal of Smart Sensors and Computing

Published Online: 26 June 2026.

J. Smart Sens. Comput., 2026, 2(2), 26210 | Volume 2 Issue 2 (June 2026) | DOI: https://doi.org/10.64189/ssc.26210

This article is licensed under Creative Commons Attribution NonCommercial 4.0 International (CC-BY-NC 4.0)

Smart Sensors and Computing: Intelligent Systems for

Healthcare and IoT Applications

Thittaporn Ganokratanaa

Department of Mathematics, Faculty of Science, King Mongkut's University of Technology, Bangkok, 10140, Thailand

*Email: eic.ssc@gr-journals.com (Thittaporn Ganokratanaa)

The rapid evolution of smart sensors, intelligent computing, embedded systems with Internet of Things ((IoT)

and wireless communication technologies, and continues to reshape the way we monitor, analyze, and interact

with the physical world.

[1-3]

Also, now days, the convergence of these technologies with artificial intelligence,

machine learning is enabling innovative solutions across healthcare, industrial automation, smart

infrastructure, and environmental monitoring.

[4,5]

As these technologies advances, interdisciplinary research

remains essential for translating scientific advances into practical, scalable, and impactful applications.

The Journal of Smart Sensors and Computing (Volume 2, Issue 2) consist of four research articles that are from

rapidly growing field, with research spanning digital healthcare, biomedical data analytics, wearable health

technologies, and large-scale wireless IoT networking.

In the present issue, Mapari et al. presents an affordable smart digital stethoscope designed to acquire heart

sounds through real-time capture and processing into data that can estimate the heart rate (BPM) and classify

heart sounds using machine learning algorithms. The system uses a modified KY-037 sound sensor and an

external electret microphone to acquire heart sounds in real time, produce waveforms of heart activity, allow

the estimation of heart beats per minute (BPM) via a machine learning classification system based on the

features of the sound signal, and are visualized using the Streamlit web application.

[6]

Yadav et al. proposed a hybrid LASSO–WOA (hLWOA) feature selection model for thyroid disease classification

that effectively reduces feature dimensionality while maintaining high predictive performance. By reducing the

feature set from 25 to just 4 informative features, the proposed approach achieved an accuracy of 99.29%,

improving model interpretability, reducing computational complexity, and enhancing classification efficiency

for intelligent clinical decision support.

[7]

Matri et al. designed HerEase, a smart wearable therapy belt that supports menstrual pain management and

personal hygiene. The device integrates heat therapy, vibration therapy, moisture monitoring, and wireless

connectivity into a comfortable, user-friendly design, demonstrating the potential of wearable technologies to

enhance women's healthcare. The wearable device consists of a heating pad to relieve menstrual cramps

through controlled heat therapy, a vibration motor to enhance comfort, and a moisture sensor that monitors

pad saturation and provides timely user alerts. The study demonstrates that a simple sensor-based control

system can deliver reliable, energy-efficient, and user-centered healthcare support.

[8]

Sayyed et al. presents a complete end-to-end hardware implementation and experimental validation of a Wi-

SUN FAN network using a Raspberry Pi Compute Module 4 (CM4) Border Router and a custom EFR32FG28-

based leaf node operating in the Indian Sub-GHz frequency band. To evaluate the practical applicability of Wi-

SUN FAN, the authors implemented and analyzed three real-world IoT use cases: crop health monitoring

through compressed image transmission, smart streetlight monitoring using energy consumption and status

reporting, and industrial equipment monitoring through vibration, temperature, and acoustic sensing. The

study demonstrates the versatility and scalability of Wi-SUN FAN for supporting reliable, low-power

communication across diverse outdoor IoT applications.

[9]

In conclusion, this issue reflects the integration of intelligent sensing systems, IoT, and AI-driven methodologies

across diverse application domains. Together, they emphasize the significance of interdisciplinary research in

advancing innovative, efficient, and scalable solutions for real-world challenges in healthcare, industry, and

smart infrastructure.

Conflict of Interest

There is no conflict of interest.

Artificial Intelligence (AI) Use Disclosure

The authors declare that artificial intelligence (AI)-assisted tools were used only for language refinement,

grammar improvement, and manuscript structuring purposes during the preparation of this work. All technical

content, experimental implementation, results, and interpretations were independently developed and verified

by the authors.

References

[1]

M. N. Bhuiyan, M. M. Rahman, M. M. Billah, D. Saha, Internet of Things (IoT): A review of its enabling

technologies in healthcare applications, standards protocols, security, and market opportunities, IEEE

Internet of Things Journal, 2021, 8, 10474-10498, doi: 10.1109/JIOT.2021.3062630.

[2]

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New England Journal of Medicine, 2016, 375, 1216–1219, doi: 10.1056/NEJMp1606181.

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environmental monitoring: Advancements, challenges, and future directions, Hygiene and

Environmental Health Advances, 2024, 12, 100114, doi: 10.1016/j.heha.2024.100114.

[6]

N. M. Mapari, A. J. Managori, H. A. Naik, M. G. Chaurasiya, T. I. Kandhal, An intelligent low-cost digital

stethoscope using Arduino, signal processing, and machine learning for real-time heart sound analysis,

Journal of Smart Sensors and Computing, 2026, 2, 26206, doi: 10.64189/ssc.26206.

[7]

A. Yadav, A. Vaishnav, M. Joshi, An efficient hybrid LASSO-WOA (hLWOA) feature selection model for

high-accuracy thyroid disease classification, Journal of Smart Sensors and Computing, 2026, 2, 26207,

doi: 10.64189/ssc.26207.

[8]

D. S. Mantri, S. Salve, D. Marathe, P. Basare, S. Tekawade, V. Bhosale, HerEase: smart period pain relief

and hygiene belt, Journal of Smart Sensors and Computing, 2026, 2, 26208, doi: 10.64189/ssc.26208.

[9]

M. A. Sayyed, S. Jafri, S. S. Shaikh, F. S. Sayed, Implementation and performance evaluation of a WI-SUN

FAN for large-scale outdoor IoT applications, Journal of Smart Sensors and Computing, 2026, 2, 26209,

doi: 10.64189/ssc.26209.

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