Indoor Campus Surveillance with HTTP Communication via Animaloid Robots
Keywords:
Animaloid, Campus, Monitoring, HTTP, Real-time, RobotsAbstract
The vision of a smart campus is fundamentally rooted in the deployment of a robust and efficient indoor monitoring system, serving as a cornerstone of its intelligent infrastructure. However, a notable limitation of current indoor surveillance is the lack of mobile monitoring capabilities, which often leaves enclosed hallways/areas insufficiently covered. To address this gap, this study proposes an enhanced surveillance framework specifically optimized for interior campus environments, leveraging HTTP-based communication and mobile telepresence animaloid robots. Designed for real-time, user-friendly operation, the system remains highly accessible within the local indoor network. Each animaloid robot is equipped with a specialized camera module to capture environmental data and stream live video feeds through a dedicated web application. The system underwent modular testing in various indoor conditions to evaluate its performance, targeting key aspects such as navigation control (robot distance from gateway), interactive responsiveness (connectivity and movement), web application performance (frame quality and latency), and operational endurance (speed and uptime). Experimental results demonstrate that the proposed system is both feasible and effective for deployment within a campus building layout. While performance remains highly dependent on local network stability and access point proximity, the findings highlight this solution as a promising platform for scalable extensions and advanced indoor functionalities in future smart campus implementations.
References
Addula, S. R., Norozpour, S., & Amin, M. (2025). Risk Assessment for Identifying Threats, vulnerabilities and countermeasures in Cloud Computing. Jordanian Journal of Informatics and Computing, 2025, 38–48. https://doi.org/10.63180/jjic.thestap.2025.1.5
Anagnostopoulos, T., Kostakos, P., Zaslavsky, A., Kantzavelou, I., Tsotsolas, N., Salmon, I., Morley, J., & Harle, R. (2021). Challenges and Solutions of Surveillance Systems in IoT-Enabled Smart Campus: A Survey. IEEE Access, 9, 131926–131954. https://doi.org/10.1109/ACCESS.2021.3114447
Antony Joe, S., Mary, S. J. J., Cordova, R., Kalash, H., & Al-Badi, A. (2023). IoT-based Smart Campus Monitoring Based on an Improved Chimp Optimization-Based Deep Belief Neural Network. Indonesian Journal of Electrical Engineering and Informatics (IJEEI), 11. https://doi.org/10.52549/ijeei.v11i1.4410
Bukhsh, M., Abdullah, S., Rahman, A., Asghar, M. N., Arshad, H., & Alabdulatif, A. (2021). An Energy-Aware, Highly Available, and Fault-Tolerant Method for Reliable IoT Systems. IEEE Access, 9, 145363–145381. https://doi.org/10.1109/ACCESS.2021.3121033
Chen, X., Xu, H., Huang, X., Wang, Y., & Wang, L. (2025). LandExplorer-1: A 3-D Survey and Monitoring Vehicle System for Natural Resources. IEEE Journal on Miniaturization for Air and Space Systems, 6(3), 215–221. https://doi.org/10.1109/JMASS.2025.3542070
Cittadini, R., Buonocore, L. R., Matheson, E., Di Castro, M., & Zollo, L. (2022). Robot-Aided Contactless Monitoring of Workers’ Cardiac Activity in Hazardous Environment. IEEE Access, 10, 133427–133438. https://doi.org/10.1109/ACCESS.2022.3231098
Eldeeb, E., & Alves, H. (2024). LoRaWAN-Enabled Smart Campus: The Data Set and a People Counter Use Case. IEEE Internet of Things Journal, 11(5), 8569–8577. https://doi.org/10.1109/JIOT.2023.3320182
Faritha Banu, J. H., R, R., M, S., & N.R, G. (2020). IoT-based Cloud Integrated Smart Classroom for a smart and sustainable Campus. Procedia Computer Science, 172, 77–81. https://doi.org/10.1016/j.procs.2020.05.012
Kulkarni, P., Hakim, Q. O. A., & Lakas, A. (2020). Experimental Evaluation of a Campus-Deployed IoT Network Using LoRa. IEEE Sensors Journal, 20(5), 2803–2811. https://doi.org/10.1109/JSEN.2019.2953572
Lampropoulos, G., & Papadakis, S. (2025). The Educational Value of Artificial Intelligence and Social Robots (pp. 3–15). https://doi.org/10.1007/978-3-031-82915-4_1
Papadakis, S., Lytvynova, S., Mintii, I., Ivanova, S., Selyshcheva, I., & Semerikov, S. (2024, March). Advancing lifelong learning with AI-enhanced ICT: A review of 3L-Person 2024.
Papadakis, S., Semerikov, S., Striuk, A., Kravtsov, H., Shyshkina, M., Marienko, M., & Danylchuk, H. (2024, March). Embracing digital innovation and cloud technologies for transformative learning experiences.
Polin, K., Yigitcanlar, T., Limb, M., & Washington, T. (2023). The Making of Smart Campus: A Review and Conceptual Framework. Buildings, 13(4). https://doi.org/10.3390/buildings13040891
Preethichandra, D. M. G., Piyathilaka, L., & Izhar, U. (2025). Review on Robotic Systems for Environmental Monitoring. IEEE Open Journal of Instrumentation and Measurement, 4, 1–17. https://doi.org/10.1109/OJIM.2024.3493875
Ramachandran, R. K., Pierpaoli, P., Egerstedt, M., & Sukhatme, G. S. (2022). Resilient Monitoring in Heterogeneous Multi-Robot Systems Through Network Reconfiguration. IEEE Transactions on Robotics, 38(1), 126–138. https://doi.org/10.1109/TRO.2021.3128313
Ramasawmy, K., & Nagowah, S. D. (2023). Smart Waste Monitoring System Using Machine Learning for IoT-enabled Smart Green Campus. 2023 11th International Conference on Information and Communication Technology (ICoICT), 505–510. https://doi.org/10.1109/ICoICT58202.2023.10262609
Razzaq, M. A., Mahar, J. A., Ahmad, M., Saher, N., Mehmood, A., & Choi, G. S. (2021). Hybrid Auto-Scaled Service-Cloud-Based Predictive Workload Modeling and Analysis for Smart Campus System. IEEE Access, 9, 42081–42089. https://doi.org/10.1109/ACCESS.2021.3065597
Shihao, L., Dahnil, D. P., & Saad, S. (2025). A Survey of Smart Campus Resource Information Management in Internet of Things. IEEE Access, 13, 66622–66645. https://doi.org/10.1109/ACCESS.2025.3558900
Sneesl, R., Jusoh, Y. Y., Jabar, M. A., & Abdullah, S. (2023). Examining IoT-Based Smart Campus Adoption Model: An Investigation Using Two-Stage Analysis Comprising Structural Equation Modeling and Artificial Neural Network. IEEE Access, 11, 125995–126026. https://doi.org/10.1109/ACCESS.2023.3331078
Suresh, M. S. S., & Menon, V. (2023). A Generic and Scalable Approach to Maximize Coverage in Diverse Indoor and Outdoor Multi-camera Surveillance Scenarios. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 53(2), 1172–1182. https://doi.org/10.1109/TSMC.2022.3194209
Ucar, C., Maloku, M., Yugay, O., & Budimir, D. (2024). IoT Motion Detection Sensors for Monitoring in a Smart Campus. 2024 13th Mediterranean Conference on Embedded Computing (MECO), 1–4. https://doi.org/10.1109/MECO62516.2024.10577922
Wang, W., Zhao, R., Mei, J., & Zheng, K. (2023). Design and Implementation of Campus Surveillance System Based on ZLMediaKit. 2023 IEEE International Conference on Advanced Learning Technologies (ICALT), 356–358. https://doi.org/10.1109/ICALT58122.2023.00110
Zahedi, Z., Sengupta, S., & Kambhampati, S. (2025). A Game-Theoretic Model of Trust in Human–Robot Teaming: Guiding Human Observation Strategy for Monitoring Robot Behavior. IEEE Transactions on Human-Machine Systems, 55(1), 37–47. https://doi.org/10.1109/THMS.2024.3488559
Zarpellon, B. O., de Oro Arenas, L., Paciência Godoy, E., Pinhabel Marafão, F., & Morales Paredes, H. K. (2024). Design and Implementation of a Smart Campus Flexible Internet of Things Architecture on a Brazilian University. IEEE Access, 12, 113705–113725. https://doi.org/10.1109/ACCESS.2024.3444471
Zhang, Y., Yip, C., Lu, E., & Dong, Z. Y. (2022). A Systematic Review on Technologies and Applications in Smart Campus: A Human-Centered Case Study. IEEE Access, 10, 16134–16149. https://doi.org/10.1109/ACCESS.2022.3148735
Zhou, Z., Yu, H., & Shi, H. (2020). Optimization of Wireless Video Surveillance System for Smart Campus Based on Internet of Things. IEEE Access, 8, 136434–136448. https://doi.org/10.1109/ACCESS.2020.3011951
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