Artificial Intelligence in Next Generation IoT Infrastructure: Challenges and Opportunities

Numerous facets of the public realm could be revolutionised by the convergence of the Internet of Things (the Internet of Things) and Artificial Intelligence (AI). This project developed a based-on data predictive maintenance system for manufacturing production lines. One of these anticipated improvements that can be included into the factory's production system is “AI of Things (AIoT),” which refers to the use of the IoT to carry out intelligent tasks with the aid of AI integration. By using the information created by IoT sensors progressively, the system utilizes machine learning (ML), a part of AI, to recognize expected blunders preceding they happen. The viability of the innovation was surveyed utilizing IoT information from genuine assembling frameworks, and the results of the appraisal demonstrated that the prescient support structure was effective in distinguishing potential failure indicators and could assist with forestalling some production stops. Comparing the performance of ML techniques revealed that frameworks of the bagging ensemble technique Random Forest and the boosting technique XGBoost appeared to outperform each of the techniques in the assessment. The factory's production system now uses the best-performing ML techniques from the present research.