IoT Data Optimization for Creating Interfaces using Chatbots on Industrial Data

This research paper explores the integration of Industrial Internet of Things (IoT) data to develop an innovative AI chatbot tailored for the industrial sector. The chatbot aims to optimize resource allocation, minimize downtime through proactive predictive maintenance, enhance energy efficiency, and provide real-time data insights. By leveraging this technology, the primary objective is to drive a transformative shift in manufacturing processes, fostering greater efficiency, sustainability, and cost-effectiveness. The research underscores the transformative potential of the AI chatbot across critical domains such as resource management, predictive maintenance, energy optimization, and analytics, emphasizing its impact on industrial operations. By analyzing existing solutions and rationale behind the chosen approach, the study elucidates how our proposed chatbot solution enhances performance and addresses key imperatives for success. Through effective implementation this solution not only yields immediate benefits but also lays the groundwork for future advancements in the field.

Authors

Publication Details

Journal
Communications on Applied Nonlinear Analysis
Published
2024-12-18
DOI
https://doi.org/10.52783/cana.v32.2869
Primary Topic
Scheduling and Optimization Algorithms
Type
article
Field-Weighted Citation Impact
0.00
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article

IoT Data Optimization for Creating Interfaces using Chatbots on Industrial Data

Priyanka Jaiswal
Communications on Applied Nonlinear Analysis
Scheduling and Optimization Algorithms
article

IoT Data Optimization for Creating Interfaces using Chatbots on Industrial Data

Priyanka Jaiswal
article en

Abstract

This research paper explores the integration of Industrial Internet of Things (IoT) data to develop an innovative AI chatbot tailored for the industrial sector. The chatbot aims to optimize resource allocation, minimize downtime through proactive predictive maintenance, enhance energy efficiency, and provide real-time data insights. By leveraging this technology, the primary objective is to drive a transformative shift in manufacturing processes, fostering greater efficiency, sustainability, and cost-effectiveness. The research underscores the transformative potential of the AI chatbot across critical domains such as resource management, predictive maintenance, energy optimization, and analytics, emphasizing its impact on industrial operations. By analyzing existing solutions and rationale behind the chosen approach, the study elucidates how our proposed chatbot solution enhances performance and addresses key imperatives for success. Through effective implementation this solution not only yields immediate benefits but also lays the groundwork for future advancements in the field.

Communications on Applied Nonlinear AnalysisVol. 32(4s)
Openalex Percentile: Top 61%
Scheduling and Optimization Algorithms
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