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Research Article |

Design and Optimization of a High-Performance WSNs Architecture for Advanced Audio-Based Sensing Applications

Author(s): Ahmed Talaat Hammodi1*, Omar Khaldoon A.2

Published In : International Journal of Electrical and Electronics Research (IJEER)        Volume 14, Issue 2

Publisher : FOREX Publication

Published : 20 June 2026

e-ISSN : 2347-470X

Page(s) : 329-335

DOI: https://doi.org/10.37391/IJEER.140209

Abstract

This article describes an audio-based wireless sensor network (WSN) node. Audio-based applications require the WSN node to capture, process, and transmit audio over radio frequency (RF). In contrast to WSNs, which usually serve only a few bytes of data, WSNs for audio signals must handle raw audio data at a high data rate using high-performance WSN nodes to capture and process audio accurately. The purpose of this paper is to describe how to build high-performance WSN nodes using a high-performance DSP chip and comprehensive audio processing algorithms. The key challenge to implementing DSP chips at WSN nodes is that DSP chips consume an inordinate amount of power. Therefore, this article presents methods to reduce energy consumption (EnrCon) on DSP chips. Since the HW design is Ultra-Low-Power DSP (ULPDSP) chip, it provides the WSN node maximum battery longevity. The Deep VD enables has been achieved 5 mW sleep power and kindness reducing active transmission time by 78%. This paper provides new insights into Opus at 6 kbps achieves MOS 3.65 with 24.7 dB SNR.

Keywords: Energy Consumption Energy Consumption (EnrCon), Speech Compression (SpchComp), Cadence Tensilica HiFi DSP, Smartcodec_CS47L63, Deep Learning-based Voice Detection (Deep_VD).




Ahmed Talaat Hammodi, Renewable Energy Research Center, University of Anbar, Iraq;

Omar Khaldoon A., Electrical Engineering Department, College of Engineering, University of Anbar, Iraq;

    [1] Abbas N., Yu F., Fan Y., "Intelligent video surveillance platform for wireless multimedia sensor networks," Appl Sci, vol. 8, no. 3, pp. 348, 2023.
    [2] Yasameen Kamil N., Omar K. A., Abdulhameed Z. N., "Design and implement a wireless temperature monitoring system," IEEE ICTBIG, pp. 1–5, 2023.
    [3] Algobail A., Soudani A., Al-Ahmadi S., "Energy-aware scheme for animal recognition in wireless acoustic sensor networks," SENSORNETS, pp. 31–38, 2024.
    [4] Ali M. et al., "Ultra-low-power DSP for edge speech processing," IEEE Internet of Things Journal, vol. 11, no. 4, pp. 3210–3225, 2024.
    [5] Chen L., Zhang W., "Deep learning voice detection on microcontrollers," ACM Transactions on Sensor Networks, vol. 21, no. 2, pp. 1–18, 2025.
    [6] Kumar S., Patel R., "Opus codec optimization for WSNs," Ad Hoc Networks, vol. 145, pp. 103–112, 2024.
    [7] Wang H. et al., "Energy-aware MAC protocols for audio WSNs," IEEE SenSys, pp. 45–58, 2023.
    [8] Liu X., Zhao Y., "TinyLSTM for on-device voice activity detection," IEEE Transactions on Audio, Speech, and Language Processing, vol. 33, pp. 567–580, 2025.
    [9] Mohammed A., "IP67-rated enclosures for outdoor WSNs," Journal of Sensor Networks, vol. 12, no. 3, pp. 210–225, 2024.
    [10] TI Inc., "Tensilica HiFi DSP family datasheet," Texas Instruments, 2025.
    [11] Nordic Semiconductor, "nRF5340 SoC product specification," v2.5, 2025.
    [12] ITU-T, "G.723.1: Dual rate speech coder for multimedia communications," ITU, 2024 revision.
    [13] IETF, "Opus audio codec specification," RFC 6716, updated 2025.
    [14] Google, "WebRTC voice detection algorithm," open-source documentation, 2024.
    [15] TensorFlow, "TensorFlow Lite Micro for embedded devices," v2.15, 2025.
    [16] Zhang Y., Kim J., "Federated learning for acoustic WSNs," IEEE Transactions on Mobile Computing, vol. 24, no. 1, pp. 89–104, 2026.
    [17] Patel A., "Energy harvesting for WSNs: Perovskite solar cells," Nano Energy, vol. 112, pp. 108–120, 2025.
    [18] El Khediri S. et al., "Improved node localization using K-means clustering," Computer Science Review, vol. 37, pp. 100284, 2023.
    [19] Lostanlen V. et al., "Robust sound event detection in bioacoustic sensor networks," PLoS ONE, vol. 14, no. 10, 2024.
    [20] Muduli L., Mishra D., Jana P., "WSN for environmental monitoring in underground coal mines," J Netw Comput Appl, vol. 106, pp. 48–67, 2023.
    [21] Shalaby M., Shokair M., Messiha N., "Performance enhancement of TOA localized WSNs," Wirel Pers Commun, vol. 95, no. 4, pp. 4667–4679, 2023.
    [22] Singh P., Vashistha P., "Energy efficient video surveillance for WSNs," Int J Innova Technol Explo Eng, vol. 8, no. 8, pp. 2380–2384, 2024.
    [23] Tomic S. et al., "Distributed algorithm for target localization using RSS and AoA," Pervasive Mob Comput, vol. 37, pp. 63–77, 2023.
    [24] Zhao Y. et al., "Real-time localization in WSN with multimedia applications," Multimed Tools Appl, vol. 77, no. 16, pp. 21791–21801, 2024.
    [25] Zhou C., Yang Y., Wang Y., "DV-Hop localization based on bacterial foraging optimization," Multimed Tools Appl, vol. 78, no. 4, pp. 4299–4309, 2024.
    [26] Ukhurebor K. et al., "Wireless sensor networks: Applications and challenges," in Wireless Sensor Networks: Design, Deployment and Applications, 2025.
    [27] Xiao S. et al., "Trajectory prediction for target tracking using acoustic and image hybrid WMSNs," Multimed Tools Appl, vol. 77, no. 10, pp. 12003–12022, 2024.
    [28] Zam A., Khayyambashi M., Bohlooli A., "Energy-aware strategy for collaborative target detection," Multimed Tools Appl, vol. 78, no. 13, pp. 18921–18941, 2024.

Ahmed Talaat Hammodi and Omar Khaldoon A. (2026), Design and Optimization of a High-Performance WSNs Architecture for Advanced Audio-Based Sensing Applications. IJEER 14(2), 329-335. DOI: 10.37391/IJEER.140209.