K S Lokesh, Dunna Nikitha Rao, C Likhitha 03 04 The use of WSNs is gaining significance in the realtime data gathering environmental monitoring and security But it is easy to be hacked into them and undermine their security and reliability An explainable ensemblebased intrusion detection system was developed using the Kaggle Wireless Sensor Network Dataset that was capable of addressing this issue In the case of hyperparameter optimization the algorithm is Particle Swarm Optimization PSO and GridSearchCV It also applies various models of machine learning including DT PSO RF PSOKNN PSO XGB PSO and a hybrid ensemble based on LightGBM and ExtraTree RF DT PSO RF KNN PSO RF KNN XGB The model results were elucidated with the help of AI methods that could be described such as LIME and SHAP which simplified the intrusion detection process The experiment indicated that the stacking ensemble performed better than any single model and accurately detected threats with 981 precision and recall and F1score It demonstrates that it is a good and comprehensible solution to WSN intrusion detection The web application is a Flaskbased application that allows users to log in and add features dynamically prepare attacks and categorize them into the list of Normals Blackhole Flooding Grayhole and TDMA Copyright (c) Journal of Science Engineering Technology and Management Science. All rights reserved 2026