Exploring the Boundaries of Connected Systems: Communications for Hard-to-Reach Areas and Extreme Conditions

The flood incidents are becoming more often and severe, thus extreme events require efficient and effective means of controlling and saving lives and property. The reason for this paper is to use Formal Modelling and Model Checking to analyse a new safety critical Flood Monitoring and Rescue System (FMRS) that shall form the basis for the efficient response to floods. Employing the TLA+ analysis, which outlines the FMRS’s dynamic behavior and operational specifications comprehensively. It is important to stress that in our work we address one of the most exciting directions of applying formal methods for the first time in collaboration with real-world safety-critical system designers and offer a powerful and transparent systematic approach to verifying safety-critical systems’ correctness, safety, and reliability. The TLA+ specifications are very carefully designed to represent multiple aspects of the FMRS, such as sensor systems, communication interfaces, as well as the rescue activity itself. To this end, we use model checking methodologies in order to assess the system’s compliance with the required safety properties, including timely detection of floods, correct delivery of data, and synchronization of rescue operations. The performed model checking demonstrates the presence of essential information about the system’s potential failure and weaknesses, which can be used for FMRS architecture improvement and development. Thus, this case shows that the best use of formal methods exist not as ad hoc methods for resolving some issues in the development of safety-critical systems, but a structured template that could be applied in other domains where high degree of assurance in the reliability of a system is needed. Besides the novel method for the better future of the field of formal verification, the proposal also sketches functional relevance of integrating the effective and efficient approaches for monitoring floods and emergency rescue operations in real-world contexts.

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Pattern Analysis on Wireless Network Coverage in DISPERKIM, South Sumatra

Al Akbar,

et al. 2024

intij

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This paper introduces a novel Heterogeneous Ensemble Machine Learning (HEML) approach designed to detect bipolar disorder, a significant healthcare challenge that demands precise and prompt diagnosis for effective treatment. The HEML method integrates multiple machines learning models, incorporating various physiological, behavioral, and contextual data from patients. By using a comprehensive feature selection technique, relevant features are extracted from each data source and utilized to train individual classifiers for detecting mental disorders. The classifiers include Adaboost, Decision Tree, K-nearest neighbors, Multilayer Perceptron, Random Forest, Relevance Vector Machine, and XGB, with Logistic Regression serving as the meta-model. This ensemble of classifiers enhances overall performance by capturing a wider range of characteristics related to mental disorders. The research evaluates the HEML method across three bipolar disorder datasets: Dataset1 (a multimodal dataset), Dataset2 (a sensor-based dataset), and Dataset3 (a real-time dataset). The HEML approach surpasses traditional methods, achieving superior accuracy rates of 95.21% with Dataset 1, 99.28% with Dataset 2, and 99% with Dataset 3. It outperforms individual models in detecting bipolar disorder, delivering the best Precision, Recall, F1 score, and Kappa Score. This comparative analysis advances the field of mental health diagnosis by leveraging the strengths of ensemble machine learning to improve accuracy and reliability in detection methods.

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Exploring the Boundaries of Connected Systems: Communications for Hard-to-Reach Areas and Extreme Conditions

Cited by 3 publications

References 92 publications

WiFoO - Practical Low-cost Free Space Optical Communication With Consumer Hardware

WiFoO - Practical Low-cost Free Space Optical Communication With Consumer Hardware

Formal Modelling and Model Checking of a Flood Monitoring and Rescue System: A Case Study of Safety-Critical System

Pattern Analysis on Wireless Network Coverage in DISPERKIM, South Sumatra

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