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Book Overview & Buying
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Table Of Contents
Hands-On Artificial Intelligence for IoT - Second Edition
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In this penultimate chapter, we explored how the fusion of AI and IIoT is revolutionizing industrial operations. The chapter detailed how smart sensors, real-time data, and advanced analytics drive predictive maintenance, energy load forecasting, and precision farming. Practical case studies and detailed code examples illustrated the use of traditional ML and DL models—such as Random Forests and LSTM networks—to predict equipment failures, optimize energy consumption, and manage industrial assets efficiently. The chapter explained techniques for failure classification and RUL prediction, emphasizing the shift from reactive to proactive maintenance strategies. Additionally, the chapter discussed electrical load forecasting using time-series analysis and LSTM models and examined how AI-driven decision-making improves fleet management and enhances safety in transportation. The integration of edge and cloud computing was highlighted as a key enabler for real-time...