Authors:
Hemarjit Ningombam,Gurumayum Robert Michael,Rajesh Bose Sudipta Majumder4,DOI NO:
https://doi.org/10.26782/jmcms.2026.06.00004Keywords:
Collaborative Acoustic Echo Mapping (CAEM),Indoor Localization,Wireless Sensor Networks,Acoustic–Radio Fusion,Non-linear Optimization,Multi-modal Sensor Fusion,Abstract
Localization of sensors in an indoor wireless sensor network (WSNs) has been a very difficult task because of attenuation of signals, multipath, and also a low supply of anchors. In this paper, we propose a new hybrid acoustic-radio system, Collaborative Acoustic Echo Mapping (CAEM), to achieve high-precision localization of sensors within an indoor environment. The proposed method combines acoustic echo data from environmental reflectors with radio-based inter-sensor ranging data, enabling simultaneous optimization of sensor and reflector locations. It considers a robust formulation based on the Huber loss to reduce the effects of measurement noise and outliers. It solves the resulting non-linear optimization problem using an efficient L-BFGS-B scheme. Extensive simulations are conducted in a 100 m x 100 m indoor space at different noise levels, anchor densities, and sensor locations. The Proposed CAEM model is compared with eight standard and contemporary strategies. Findings indicate that CAEM consistently outperforms traditional methods, minimizing localization error by up to 3.2 times. In a representative scenario, CAEM achieves an RMSE of 11.33 m, which is far better than the baselines. The results emphasise the utility of the acoustic and radio modalities approach for robust, scalable indoor localisation, making CAEM a promising solution for next-generation IoT and WSN applications.Refference:
I. Abdel-Basset, M., Chang, V., Hawash, H., Chakrabortty, R. K., & Ryan, M. J. (2024). Deep learning approaches for human-centered IoT applications in smart indoor environments: A contemporary survey. Annals of Operations Research, 339(1–2), 3–51. 10.1007/s10479-021-04164-3
II. Abdulhussein Abdulzahra, S., & Al-Qurabat, K. M. (2024). Exploring radio frequency-based UAV localization techniques: A comprehensive review. International Journal of Computing and Digital Systems, 15(1), 1565–1581. 10.12785/ijcds/1501111
III. Adnan, M., Razzaque, M., Ahmed, I., & Isnin, I. (2013). Bio-mimic optimization strategies in wireless sensor networks: A survey. Sensors, 14(1), 299–345. 10.3390/s140100299
IV. Ahmad, N. S. (2024). Recent advances in WSN-based indoor localization: A systematic review of emerging technologies, methods, challenges, and trends. IEEE Access, 12, 180674–180714. 10.1109/ACCESS.2024.3509516
V. Alameda-Pineda, X., Staiano, J., Subramanian, R., Batrinca, L., Ricci, E., Lepri, B., Lanz, O., & Sebe, N. (2016). SALSA: A novel dataset for multi-modal group behavior analysis. IEEE Transactions on Pattern Analysis and Machine Intelligence, 38(8), 1707–1720. 10.1109/TPAMI.2015.2496269
VI. Ali, J., Kaemarungsi, K., Phakaew, T., Uzair, M., Narbudowicz, A., & Chalermwisutkul, S. (2024). Low-cost indoor localization using dual-chip RFID tag. IEEE Open Journal of Antennas and Propagation, 5, 1209–1220. 10.1109/OJAP.2024.3372030
VII. Ali, R., Liu, R., He, Y., Nayyar, A., & Qureshi, B. (2021). Multi-object identification and localization review. IEEE Access, 9, 122924–122950. 10.1109/ACCESS.2021.3108775
VIII. Aman, M., Li, F., Khan, Z., Khan, F., Khan, J., & Khan, S. (2025). Modern localization in UWSNs with machine learning integration. Scientific Reports, 15(1). 10.1038/s41598-025-89916-y
IX. Amjad, B., Ahmed, Q. Z., Lazaridis, P. I., Hafeez, M., Khan, F. A., & Zaharis, Z. D. (2023). Radio SLAM: A review on radio-based simultaneous localization and mapping. IEEE Access, 11, 9260–9278. 10.1109/ACCESS.2023.3237330
X. Andò, B., Baglio, S., Crispino, R., & Marletta, V. (2021). Indoor localization techniques: Multi-trilateration-based system. Applied Sciences, 11(16), 7392. 10.3390/app11167392
XI. Bibbò, L., Carotenuto, R., & Della Corte, F. (2022). An Overview of Indoor Localization System for Human Activity Recognition (HAR) in Healthcare. Sensors, 22(21), 8119. 10.3390/s22218119
XII. Cha, K., Lee, J., Özger, M., & Lee, W. (2023). When wireless localization meets artificial intelligence: Basics, challenges, synergies, and prospects. Applied Sciences, 13(23), 12734. 10.3390/app132312734
XIII. Chen, X., & Zhang, B. (2012). Improved DV-Hop Node Localization Algorithm in Wireless Sensor Networks. International Journal of Distributed Sensor Networks. 10.1155/2012/213980
XIV. Cui, H., Wang, S., & Zhou, C. (2023). A high-accuracy and low-energy range-free localization algorithm for wireless sensor networks. EURASIP Journal on Wireless Communications and Networking, 2023, Article 37. 10.1186/s13638-023-02246-3
XV. Cui, J., Shang, Y., Yu, S., & Wang, Y. (2024). Research on intelligent wheelchair multimode human–computer interaction and assisted driving technology. Actuators, 13(6), Article 230. https://doi.org/10.3390/act13060230
XVI. Dagher, R., & Quilez, R. (2014). Localization in wireless sensor networks. In Wireless Sensor Networks (Chapter 9). 10.1142/9789814551342_0009
XVII. Dai, J., Wang, M., Wu, B., Shen, J., & Wang, X. (2023). Survey of Wi-Fi assisted indoor positioning techniques. Sensors, 23(18), 7961. 10.3390/s23187961
XVIII. Das, S., Malik, P., & Pandey, A. (2025). Advances in underwater sonar systems and AI-driven signal processing. Journal of Field Robotics, 43(2), 899–931. 10.1002/rob.70077
XIX. De Cock, C., Joseph, W., Martens, L., Trogh, J., & Plets, D. (2021). Multi-Floor Indoor Pedestrian Dead Reckoning with a Backtracking Particle Filter and Viterbi-Based Floor Number Detection. Sensors, 21(13), 4565. 10.3390/s21134565
XX. Deshmukh, R. A., Hasamnis, M. A., Kulkarni, M. B., & Bhaiyya, M. (2025). Advancing indoor positioning systems: innovations, challenges, and applications in mobile robotics. Robotica, 43(7), 2710–2750. 10.1017/S0263574725101872
XXI. Ejaz, M., Bakar, K., Fauzi, I., Isyaku, B., Abdalla, T., Abdelmaboud, A., & Abbas, A. (2024). Elevating Localization Accuracy in Wireless Sensor Networks: A Refined DV-Hop Approach. Computers, Materials & Continua, 81(1), 1511–1528. 10.32604/cmc.2024.054938
XXII. Elsanhoury, M., Mäkelä, P., Koljonen, J., Välisuo, P., Shamsuzzoha, A., Mantere, T., Elmusrati, M., & Kuusniemi, H. (2022). Precision positioning for smart logistics using ultra-wideband technology-based indoor navigation: A review. IEEE Access, 10, 44413–44445. 10.1109/ACCESS.2022.3169267
XXIII. Farid, Z., Nordin, R., & Ismail, M. (2013). Recent advances in wireless indoor localization techniques and systems. Journal of Computer Networks and Communications, 2013, 1–12. 10.1155/2013/185138
XXIV. Fawad, M., Khan, M. Z., Ullah, K., Alasmary, H., Shehzad, D., & Khan, B. (2023). Enhancing Localization Efficiency and Accuracy in Wireless Sensor Networks. Sensors, 23(5), 2796. 10.3390/s23052796
XXV. Fen, L., Liu, J., Yin, Y., Wang, W., Dong-hai, H., Chen, P., et al. (2020). Survey on WiFi-based indoor positioning techniques. IET Communications, 14(9), 1372–1383. 10.1049/iet-com.2019.1059
XXVI. Fischer, G., Bordoy, J., Schott, D., Xiong, W., Gabbrielli, A., Höflinger, F., et al. (2022). Multi-modal indoor localization using ultrasonic and BLE data. IEEE Sensors Journal, 22(6), 5857–5868. 10.1109/JSEN.2022.3148529
XXVII. Gabela, J., et al. (2019). UWB-based cooperative positioning system evaluation. Sensors, 19(23), 5274. 10.3390/s19235274
XXVIII. Geok, T., Aung, K., Aung, M., Min, T., Abdaziz, A., Liew, C., et al. (2020). Review of indoor positioning using radio wave technology. Applied Sciences, 11(1), 279. 10.3390/app11010279
XXIX. Gupta, A., & Singh, U. (2023). Performance evaluation of sensor node localization. Wireless Personal Communications, 131(2), 941–954. 10.1007/s11277-023-10462-9
XXX. Hadir, A., Kaabouch, N., El Houssaini, M.-A., & El Kafi, J. (2023). Range-free localization approaches based on intelligent swarm optimization for Internet of Things. Information, 14(11), 592. 10.3390/info14110592
XXXI. Hailu, T., Guo, X., & Si, H. (2025). Indoor positioning systems as critical infrastructure: An assessment for enhanced location-based services. Sensors, 25(16), 4914. https://doi.org/10.3390/s25164914
XXXII. Han, F., Mohamed, I., Liu, X., Ghazali, K., & Wang, H. (2020). Hybrid range-free localization using dynamic communication range. International Journal of Online and Biomedical Engineering, 16(8), 4–24. 10.3991/ijoe.v16i08.14379
XXXIII. He, L., & Kang, Z. (2015). Weighted APIT localization algorithm based on vector similarity. Proceedings of the International Conference on Computer Science and Intelligent Communication. https://doi.org/10.2991/csic-15.2015.3
XXXIV. Heshmat, M., Saoud, L., Abujabal, M., Sultan, A., Elmezain, M., Seneviratne, L., et al. (2025). Underwater SLAM with deep learning: Challenges and future directions. Sensors, 25(11), 3258. 10.3390/s25113258
XXXV. Huang, J., Wang, Y., Zou, Y., Wu, K., & Ni, L. (2023). Ubiquitous WiFi and acoustic sensing: Principles and applications. Journal of Computer Science and Technology, 38(1), 25–63. 10.1007/s11390-023-3073-5
XXXVI. Huang, P., Chen, J., Larosa, Y., & Chiang, T. (2011). Distributed Fermat-point localization for wireless sensor networks. Sensors, 11(4), 4358–4371. 10.3390/s110404358
XXXVII. Jiao, J. (2021). Mobile industrial robots localization using RSSI and multidimensional scaling. Advances in Multimedia, 2021, 1–9. 10.1155/2021/2437224
XXXVIII. Józefczak, A. (2012). Chronicle: Open seminar on acoustics. Archives of Acoustics, 37(3), 373–393. 10.2478/v10168-012-0047-y
XXXIX. Kamal, Y., Sharma, K., & Vandana, V. (2019). H-best particle swarm optimization-based localization algorithm for wireless sensor networks. International Journal of Engineering and Advanced Technology, 9(1), 2769–2778. 10.35940/ijeat.a9776.109119
XL. Kanhere, O., & Rappaport, T. S. (2018). Position locationing for millimeter wave systems. In Proceedings of the 2018 IEEE Global Communications Conference (GLOBECOM) (pp. 206–212). IEEE. 10.1109/GLOCOM.2018.8647983
XLI. Kapoor, R., Ramasamy, S., Gardi, A., Schyndel, R., & Sabatini, R. (2018). Acoustic sensors for navigation applications. Sensors, 18(2), 499. 10.3390/s18020499
XLII. Kaur, T., Singh, J., & Singh, M. (2025). Optimization-driven localization in wireless sensor networks: A comprehensive review. International Journal of Communication Systems, 38(14). 10.1002/dac.70213
XLIII. Khan, F., Awais, M., Rasheed, M., Masood, B., & Ghadi, Y. (2021). Comparison of wireless standards in IoT for indoor localization. IEEE Access, 9, 65925–65933. 1109/ACCESS.2021.3076371
XLIV. Khider, M., Kaiser, S., & Robertson, P. (2012). A novel three-dimensional movement model for pedestrian navigation. The Journal of Navigation, 65(2), 245–264. 10.1017/S0373463311000713
XLV. Le, N., & Jang, Y. (2019). Photography trilateration indoor localization with image sensor communication. Sensors, 19(15), 3290. 10.3390/s19153290
XLVI. Li, X., Chen, L., Wang, J., Chu, Z., Li, Q., & Sun, W. (2015). Fuzzy system and improved APIT-based range-free localization method. KSII Transactions on Internet and Information Systems, 9(7). 10.3837/tiis.2015.07.005
XLVII. Lin, A., Jiang, T., Kanwal, J., Lu, G., Luo, J., Wei, X., et al. (2014). Echolocation vocalization variation in bats. Oikos, 124(3), 364–371. 10.1111/oik.01604
XLVIII. Liouane, H., Messous, S., Cheikhrouhou, O., Baz, M., & Hamam, H. (2021). Regularized least square multi-hop localization algorithm. IEEE Access, 9, 136406–136418. 10.1109/ACCESS.2021.3116767
XLIX. Liu, J., Yang, Z., Zlatanova, S., Li, S., & Yu, B. (2025). Smartphone indoor localization using multi-source sensor fusion. Sensors, 25(6), 1806. 10.3390/s25061806
L. Liu, S., Chen, Y., Trappe, W., & Greenstein, L. (2009). Non-interactive localization of cognitive radios based on dynamic signal strength mapping. Proceedings of the 6th Annual IEEE Communications Society Conference on Sensor, Mesh and Ad Hoc Communications and Networks. 10.1109/WONS.2009.4801847
LI. Lloret, J., Tomas, J., Garcia, M., & Canovas, A. (2009). A Hybrid Stochastic Approach for Self-Location of Wireless Sensors in Indoor Environments. Sensors, 9(5), 3695–3712. 10.3390/s90503695
LII. Madhumathi, K., Suresh, T., & Maruti, R. (2020). Node localization using Naive Bayes and trilateration. International Journal of Engineering and Advanced Technology, 9(3), 2467–2470. 10.35940/ijeat.c5604.029320
LIII. Maghdid, S., & Maghdid, H. (2021). Comprehensive review of indoor/outdoor localization solutions in IoT. TechRxiv. 10.36227/techrxiv.15138609
LIV. Majeed, A., Gulzari, M., Mu'azzah, N., & Abbas, A. (2024). Indoor positioning based on UWB and Li-Fi technologies: A review. Elektrika Journal of Electrical Engineering, 23(1), 18–30. 10.11113/elektrika.v23n1.431
LV. Martin-Escalona, I., & Zola, E. (2020). Passive Round-Trip-Time Positioning in Dense IEEE 802.11 Networks. Electronics, 9(8), 1193. 10.3390/electronics9081193
LVI. Mass-Sanchez, J., et al. (2018). Factorial design analysis for localization algorithms. Applied Sciences, 8(12), 2654. 10.3390/app8122654
LVII. Messous, S., & Liouane, H. (2019). Online Sequential DV-Hop Localization Algorithm for Wireless Sensor Networks. Mobile Information Systems, 2020(1), 8195309. 10.1155/2020/8195309
LVIII. Misra, P., Kottege, N., Kusý, B., Ostry, D., & Jha, S. (2013). Acoustical ranging techniques in wireless sensor networks. ACM Transactions on Sensor Networks, 10(1), 1–38. 10.1145/2529981
LIX. Moradbeikie, A., et al. (2021). GNSS-free outdoor localization techniques for IoT. Applied Sciences, 11(22), 10793. 10.3390/app112210793
LX. Nessa, A., Adhikari, B., Hussain, F., & Fernando, X. (2022). A survey of machine learning for indoor positioning. 10.32920/21476622
LXI. Prorok, A., & Martinoli, A. (2014). Accurate indoor localization with ultra-wideband using spatial models and collaboration. The International Journal of Robotics Research, 33(4), 547–568. 10.1177/0278364913500301
LXII. Qi, L., Liu, Y., Yu, Y., Chen, L., & Chen, R. (2024). Current status and future trends of meter-level indoor positioning technology. Remote Sensing, 16(2), 398. 10.3390/rs16020398
LXIII. Qi, X., Liu, X., & Liu, L. (2018). Combined localization algorithm for wireless sensor networks. Mathematical Problems in Engineering, 2018, Article ID 4648109. 10.1155/2018/4648109
LXIV. Qiao, D., & Pang, G. (2014). Evolutionary approach on connectivity-based sensor network localization. Applied Soft Computing, 22, 36–46. 10.1016/j.asoc.2014.04.019
LXV. Rathnayake, R., Maduranga, M., Tilwari, V., & Dissanayake, M. (2023). RSSI and machine learning-based indoor localization systems for smart cities. Engineering Advances, 4(2), 1468–1494. 10.3390/eng4020085
LXVI. Retscher, G., & Leb, A. (2021). Smartphone-based indoor navigation using Wi-Fi fingerprinting. Sensors, 21(2), 432. 10.3390/s21020432
LXVII. Rizk, H., Elmogy, A., & Yamaguchi, H. (2022). A Robust and Accurate Indoor Localization Using Learning-Based Fusion of Wi-Fi RTT and RSSI. Sensors, 22(7), 2700. 10.3390/s22072700
LXVIII. Savić, T., Vilajosana, X., & Watteyne, T. (2022). Constrained localization: A survey. IEEE Access, 10, 49297–49321. 10.1109/ACCESS.2022.3171859
LXIX. Shan, Z., & Yum, T. (2007). Precise localization with smart antennas in ad-hoc networks. In Proceedings of IEEE GLOBECOM 2007. 10.1109/GLOCOM.2007.203
LXX. Shang, J., Hu, X., Gu, F., Wang, D., & Yu, S. (2015). Improvement schemes for indoor mobile location estimation: A survey. Mathematical Problems in Engineering, 2015, Article ID 397298. 10.1155/2015/397298
LXXI. Simões, W., Machado, G., Sales, A., Lucena, M., Jazdi, N., & Lucena, V. (2020). Indoor navigation systems for visually impaired: A review. Sensors, 20(14), 3935. 10.3390/s20143935
LXXII. Singh, J., Farnham, T., & Wang, Q. (2023). When BLE meets light: Multi-modal fusion for enhanced indoor localization. In Proceedings of the 29th Annual International Conference on Mobile Computing and Networking (MobiCom ’23), Article 139, 1–3. Association for Computing Machinery. 10.1145/3570361.3615746
LXXIII. Singh, S., & Sharma, R. M. (2016). Optimization techniques in wireless sensor networks. In Proceedings of the Second International Conference on Information and Communication Technology for Competitive Strategies (ICTCS ’16), Article 140, 1–7. Association for Computing Machinery. 10.1145/2905055.2905200
LXXIV. Smoleń, M., & Augustyniak, P. (2020). Assisted Living System with Adaptive Sensor’s Contribution. Sensors, 20(18), 5278. 10.3390/s20185278
LXXV. Soundari, D., & Poongodi, C. (2024). Hybrid bat–sand cat swarm optimization-based node localization. International Journal of Communication Systems, 38(2). 10.1002/dac.5961
LXXVI. Stone, K., & Camp, T. (2012). A survey of distance-based wireless sensor network localization techniques. International Journal of Pervasive Computing and Communications, 8(2), 158–183. 10.1108/17427371211245373
LXXVII. Sun, Y., Finnerty, P., & Ohta, C. (2024). BLE-based outdoor localization with optimization algorithms. IEEE Access, 12, 45164–45175.
10.1109/ACCESS.2024.3380897
LXXVIII. Swain, M., et al. (2021). LoRa-based link budget optimization for IoT. Agronomy, 11(5), 820. 10.3390/agronomy11050820
LXXIX. Trịnh, Q., Golio, N., Cheng, Y., Cha, H., Tai, K., Ouyang, L., et al. (2025). Sonochemistry and sonocatalysis: Current progress and future opportunities. Green Chemistry, 27(18), 4926–4958. 10.1039/D5GC01098E
LXXX. Wei, X., Wei, Z., & Radu, V. (2021). Sensor-Fusion for Smartphone Location Tracking Using Hybrid Multi-modal Deep Neural Networks. Sensors, 21(22), 7488. 10.3390/s21227488
LXXXI. Wei, X., Wei, Z., & Radu, V. (2021). MM-Loc: Cross-sensor indoor smartphone location tracking using multi-modal deep neural networks. In 2021 International Conference on Indoor Positioning and Indoor Navigation (IPIN) (pp. 1–8). IEEE. 10.1109/IPIN51156.2021.9662519
LXXXII. Wong, A., Whitehill, T., Ma, E., & Masters, R. (2012). Effects of errorless learning on velopharyngeal movement control. Journal of the Acoustical Society of America, 131(4), 3273. 10.1121/1.4708235
LXXXIII. Woock, P., & Frey, C. (2010). Deep-sea AUV navigation using sonar-based SLAM. In Proceedings of OCEANS 2010 Sydney. 10.1109/OCEANSSYD.2010.5603528
LXXXIV. Xiong, J., Sundaresan, K., & Jamieson, K. (2015). ToneTrack: Leveraging Frequency-Agile Radios for Time-Based Indoor Wireless Localization. In Proceedings of the 21st Annual International Conference on Mobile Computing and Networking (MobiCom ’15) (pp. 537–549). Association for Computing Machinery. 10.1145/2789168.2790125
LXXXV. Xu, X., Tang, Y., & Li, S. (2017). Indoor localization based on hybrid Wi-Fi hotspots. In 2017 International Conference on Indoor Positioning and Indoor Navigation (IPIN). 10.1109/IPIN.2017.8115924
LXXXVI. Yadav, P., & Sharma, S. (2022). A systematic review of localization in WSN: Machine learning and optimization-based approaches. International Journal of Communication Systems, 36(4). 10.1002/dac.5397
LXXXVII. Yang, F., Song, W., Zhang, C., Fang, H., Min, C., & Yuan, X. (2021). Phase-shifted surface plasmon resonance sensor for photoacoustic imaging. ACS Sensors, 6(5), 1840–1848. 10.1021/acssensors.1c00029
LXXXVIII. Yang, T., Cabani, A., & Chafouk, H. (2021). A Survey of Recent Indoor Localization Scenarios and Methodologies. Sensors, 21(23), 8086. 10.3390/s21238086
LXXXIX. Zhang, X., Yao, X., Hui, L., Song, F., & Hu, F. (2021). A Bibliometric Narrative Review on Modern Navigation Aids for People with Visual Impairment. Sustainability, 13(16), 8795. 10.3390/su13168795
XC. Zhao, H., Shi, H., & Zhao, Y. (2013). Range-free localization algorithm in wireless sensor networks with asymmetric links. Applied Mechanics and Materials, 446–447, 1591–1595. 10.4028/www.scientific.net/AMM.446-447.1591
XCI. Zhao, Y., & Smith, J. (2013). Battery-free RFID-based indoor acoustic localization platform. In IEEE International Conference on RFID 2013. 10.1109/RFID.2013.6548143
XCII. Zheng, J., Chen, L., & Xia, X. (2016). Localization algorithm based on improved DV-Hop. In Proceedings of the International Conference on Electronics, Network and Computer Engineering (ICENCE 2016). 10.2991/icence-16.2016.83