LOW-POWER MULTI-SENSOR EXTENSION FOR WEMOS CONTROLLERS USING MULTIPLEXED ANALOG INPUTS

Zuly Budiarso Budiarso; Muji Sukur; Eddy Nurraharjo; saefurrohman

doi:10.34288/jri.v7i3.358

Authors

Zuly Budiarso Budiarso Universitas Stikubank Semarang
Muji Sukur Universitas Stikubank Semarang
Eddy Nurraharjo Universitas Stikubank Semarang https://orcid.org/0000-0003-2015-5993
saefurrohman Universitas Stikubank Semarang

(*) Corresponding Author

DOI:

https://doi.org/10.34288/jri.v7i3.358

Keywords:

WeMOS D1, analog multiplexer, low-power IoT, sensor expansion, embedded systems

Abstract

The increasing demand for low-cost, compact, and energy-efficient IoT systems has highlighted the limitations of microcontroller units (MCUs) such as the WeMOS D1 Mini, which are constrained by a single analog input pin. This is a major challenge for applications that require multiple analog sensors, such as environmental monitoring or smart agriculture. This paper presents a hardware-based solution using the CD74HC4067 16-channel analog multiplexer to expand the analog input capacity of the WeMOS controller. The system architecture allows multiple sensors to share a single analog input managed by digital control lines. The experimental implementation used six Light Dependent Resistor (LDR) sensors to evaluate accuracy, latency, and power efficiency. The results show that sensor reading accuracy remains within ±2% deviation, with an average channel switching latency of 42 milliseconds and only a 5% increase in total power consumption compared to a single sensor system. These results confirm that the multiplexing strategy maintains reliable performance while significantly improving scalability without compromising power constraints. The proposed approach provides a robust, low-power, and low-cost method for multi-sensor deployment on constrained MCUs, enabling broader application in resource-constrained IoT systems. Future developments may include cascading multiple multiplexers and integrating wireless data transmission for remote sensing applications.

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References

Atawi, A. A., S. Alyahyan, M. N. Alatawi, T. Sadad, T. Manzoor, M. Farooq-I-Azam, and Z. H. Khan. 2023. “Stress Monitoring Using Machine Learning, IoT and Wearable Sensors.” Sensors (Basel, Switzerland) 23(21). doi: 10.3390/s23218875.

Al-Talb, Heba N. Y., Sama N. M. Al-Faydi, Toka A. Fathi, and Maan A. S. Al-Adwany. 2023. “A Fuzzy Logic IoT- Based Temperature and Humidity Control System for Smart Buildings.” International Journal of Computing and Digital Systems 13(1):139–47. doi: 10.12785/ijcds/13011.

Ance, Azis Steven, Salmawaty Tansa, Iskandar Zulkarnain Nasibu, Syahrir Abdussamad, and Amirudin Yunus Dako. 2023. “Rancang Bangun Prototipe Loss Daya Listrik Bersakala Rumah Tangga Berbasis Arduino ESP8266.” Jambura Journal of Electrical and Electronics Engineering 5:228–33. doi: 10.37905/jjeee.v5i2.14474.

Dos Anjos, J. C. S., J. L. G. Gross, K. J. Matteussi, G. V. González, V. R. Q. Leithardt, and C. F. R. Geyer. 2021. “An Algorithm to Minimize Energy Consumption and Elapsed Time for Iot Workloads in a Hybrid Architecture.” Sensors 21(9). doi: 10.3390/s21092914.

Dwivedi, A. K., P. S. Mehra, O. Pal, M. N. Doja, and B. Alam. 2021. “EETSP: Energy-Efficient Two-Stage Routing Protocol for Wireless Sensor Network-Assisted Internet of Things.” International Journal of Communication Systems 34(17). doi: 10.1002/dac.4965.

Fletcher, Reginald S., and Daniel K. Fisher. 2018. “A Miniature Sensor for Measuring Reflectance, Relative Humidity, and Temperature: A Greenhouse Example.” Agricultural Sciences 09(11):1516–27. doi: 10.4236/as.2018.911106.

Garg, A., and M. Jailia. 2020. “A Resilient and Scalable Novel Protocol for Wireless Sensor Networks-Maximum Energy Clustering (Mec).” Indian Journal of Computer Science and Engineering 11(6):859–70. doi: 10.21817/indjcse/2020/v11i6/201106190.

De Giovanni, E., A. A. Valdes, M. Peon-Quiros, A. Aminifar, and D. Atienza. 2021. “Real-Time Personalized Atrial Fibrillation Prediction on Multi-Core Wearable Sensors.” IEEE Transactions on Emerging Topics in Computing 9(4):1654–66. doi: 10.1109/TETC.2020.3014847.

Jung, W., and H. G. Lee. 2022. “Energy–Accuracy Aware Finger Gesture Recognition for Wearable IoT Devices.” Sensors 22(13). doi: 10.3390/s22134801.

Kalpana, Y. B., J. Nirmaladevi, R. Sabitha, S. G. Ammal, B. Dhiyanesh, and R. Radha. 2024. Revolutionizing Agriculture: Integrating IoT Cloud, and Machine Learning for Smart Farm Monitoring and Precision Agriculture. Vol. 1170.

Kethineni, K., and P. Gera. 2023. “Iot-Based Privacy-Preserving Anomaly Detection Model for Smart Agriculture.” Systems 11(6). doi: 10.3390/systems11060304.

Kishorebabu, V., and R. Sravanthi. 2020. “Real Time Monitoring of Environmental Parameters Using IOT.” Wireless Personal Communications 112(2):785–808. doi: 10.1007/s11277-020-07074-y.

Ouni, R., and K. Saleem. 2022. “Framework for Sustainable Wireless Sensor Network Based Environmental Monitoring.” Sustainability (Switzerland) 14(14). doi: 10.3390/su14148356.

Pezeshki, Zahra, Sayyed M. Mazinani, and Elnaz Omidvar. 2022. “Outdoor Temperature Estimation Using ANFIS for Soft Sensors.” Journal of Autonomous Intelligence 2(2):53. doi: 10.32629/jai.v2i3.58.

Płaczek, B. 2024. “Prediction-Based Data Reduction with Dynamic Target Node Selection in IoT Sensor Networks.” Future Generation Computer Systems 152:225–38. doi: 10.1016/j.future.2023.11.007.

Praveenchandar, J., D. Vetrithangam, S. Kaliappan, M. Karthick, N. K. Pegada, P. P. Patil, S. G. Rao, and S. Umar. 2022. “IoT-Based Harmful Toxic Gases Monitoring and Fault Detection on the Sensor Dataset Using Deep Learning Techniques.” Scientific Programming 2022. doi: 10.1155/2022/7516328.

Rashid, A., T. Pecorella, and F. Chiti. 2020. “Toward Resilient Wireless Sensor Networks: A Virtualized Perspective.” Sensors 20(14):1–20. doi: 10.3390/s20143902.

Rastogi, Krati, and Divya Lohani. 2022. “Context-Aware IoT-Enabled Framework to Analyse and Predict Indoor Air Quality.” Intelligent Systems with Applications 16. doi: 10.1016/j.iswa.2022.200132.

Rathi, S., and S. S. Borkotoky. 2024. “Energy-Efficient and Latency-Aware Message Replica Transmission in IoT Networks.” IEEE Transactions on Industrial Informatics 20(4):6573–81. doi: 10.1109/TII.2023.3346999.

Samal, A., L. Samal, A. K. Swain, and K. Mahapatra. 2023. “Integrated IoT-Based Air Quality Monitoring and Prediction System: A Hybrid Approach.” Pp. 441–44 in Proceedings - 2023 IEEE International Symposium on Smart Electronic Systems, iSES 2023.

Santos, B., A. Soares, T. A. Nguyen, D. K. Min, J. W. Lee, and F. A. Silva. 2021. “IoT Sensor Networks in Smart Buildings: A Performance Assessment Using Queuing Models.” Sensors 21(16). doi: 10.3390/s21165660.

Shao, W., Y. Wei, P. Rajapaksha, D. Li, Z. Luo, and N. Crespi. 2023. “Low-Latency Dimensional Expansion and Anomaly Detection Empowered Secure IoT Network.” IEEE Transactions on Network and Service Management 20(3):3865–79. doi: 10.1109/TNSM.2023.3246798.

Siddiquee, K. N. E. A., M. S. Islam, N. Singh, V. K. Gunjan, W. H. Yong, M. N. Huda, and D. S. B. Naik. 2022. “Development of Algorithms for an IoT-Based Smart Agriculture Monitoring System.” Wireless Communications and Mobile Computing 2022. doi: 10.1155/2022/7372053.

Simo, A., S. Dzitac, A. Duțu, and I. Pandelica. 2023. “Smart Agriculture in the Digital Age: A Comprehensive IoT-Driven Greenhouse Monitoring System.” International Journal of Computers, Communications and Control 18(6). doi: 10.15837/ijccc.2023.6.6147.

Valsalan, P., N. U. Hasan, I. Baig, and M. Zghaibeh. 2022. “Remote Healthcare Monitoring Using Expert System.” International Journal of Advanced Computer Science and Applications 13(3):593–99. doi: 10.14569/IJACSA.2022.0130370.

Zivelonghi, A., and A. Giuseppi. 2024. “Smart Healthy Schools: An IoT-Enabled Concept for Multi-Room Dynamic Air Quality Control.” Internet of Things and Cyber-Physical Systems 4:24–31. doi: 10.1016/j.iotcps.2023.05.005.