# Adaptive Jamming Mitigation for Clustered Energy-Efficient LoRa-BLE Hybrid Wireless Sensor Networks
## 1 Introduction
Analyzing energy consumption under different jamming scenarios enables researchers to design intelligent mitigation strategies that optimize duty cycling, adaptive transmission rates, and selective protocol switching, ensuring that energy resources are allocated efficiently without compromising security. Furthermore, energy-aware jamming mitigation techniques, such as AI-driven anomaly detection and adaptive power control, provide a balance between resilience and energy conservation, ensuring that countermeasures do not introduce excessive energy overhead [16]. As HWSNs continue to be deployed in critical applications such as industrial automation, smart cities, and environmental monitoring, the development of energy-efficient anti-jamming mechanisms will be essential to maintaining sustainable and secure communication infrastructures. This study introduces an experimental framework that integrates CC1352P and LPSTK-CC1352R sensors in a heterogeneous IoT network, combining LoRa and BLE connectivity to evaluate jamming resilience in real-world conditions. The methodology involves deploying sensor nodes across different indoor and outdoor environments within a university campus, including laboratories, classrooms, offices, and green areas, where interference sources such as Wi-Fi networks, mobile devices, and electronic equipment are present. By implementing a cluster-based mitigation model, sensor nodes dynamically elect a cluster head (CH) based on energy availability, signal quality, and retransmission rates, ensuring that network coordination is handled by the most resilient node. This adaptive approach enables the system to detect jamming events using a combination of packet delivery success rate, RSSI variations, and energy consumption anomalies, triggering real-time network reconfiguration strategies to maintain connectivity and optimize energy efficiency [17]. The key contributions of this work are as follows: (i) an experimental evaluation of jamming attacks in a heterogeneous LoRa-BLE network; (ii) the development of an energy-aware cluster-based mitigation strategy; (iii) a dynamic communication switching mechanism that ensures network resilience by adapting to interference conditions; and (iv) the integration of real-time metrics to detect and mitigate jamming using an energy consumption model. The proposed methodology is validated through real-world experiments in a controlled yet realistic environment, providing insights into the impact of jamming on multi-protocol IoT networks and the effectiveness of the mitigation strategies. This study contributes to advancing secure and energy-efficient WSN deployments, offering a practical solution for mitigating interference-based attacks in diverse IoT applications [18]. This paper is structured as follows. Section 2 provides a comprehensive review of related work, highlighting existing jamming mitigation strategies and their limitations in HWSNs. Section 3 details the materials and methods, including the experimental setup, sensor selection, and network architecture that integrates LoRa and BLE. Section 4 presents the proposed jamming detection and mitigation strategy, emphasizing cluster-based adaptive switching and real-time interference response mechanisms. Section 5 discusses the results obtained from controlled experiments, comparing the performance of the proposed strategy against conventional mitigation techniques in terms of energy efficiency, retransmission rates, and network resilience. Finally, We conclude the study by summarizing key findings and outlining future research directions to enhance jamming resilience in multi-protocol IoT environments.