Improving occupational safety through assessment of Indian waste disposal sites and stakeholder engagement

In India’s solid waste disposal facilities, occupational safety remains a pressing concern. This research delves into an integrative approach combining advanced sensor technologies, Internet of Things (IoT), and machine learning algorithms—namely Support Vector Machine (SVM), Random Forest (RF), and Convolutional Neural Network (CNN)—to enhance safety protocols. These algorithms were used to analyze data from the waste disposal sites, identifying potential hazards and predicting safety risks. The results were promising: CNN displayed a remarkable 98% accuracy in identifying hazardous conditions, SVM followed closely at 95.5%, and RF achieved 93%. Furthermore, the study emphasized the significance of engaging primary stakeholders, with data showing robust participation and satisfaction rates among workers, management, and regulatory bodies. The integration of technology with stakeholder collaboration revealed an effective strategy to not only detect but also proactively address potential safety hazards. The study underscores the potential of innovative technologies coupled with stakeholder involvement in transforming safety measures at waste disposal sites in India, aiming for a reduction in occupational hazards and the promotion of a safer working environment.