Real-time Decision System Customer Perceived Value (Cpv) Via Internet of Things (Iot) and Explainable Ai (Xai)

Harshith C; Thanush B J; Aryan Aiyappa; Anjali Bhardwaj

doi:10.36948/ijfmr.2025.v07i05.59281

Real-time Decision System Customer Perceived Value (Cpv) Via Internet of Things (Iot) and Explainable Ai (Xai)

Author(s)	Prof. Harshith C, Mr. Thanush B J, Mr. Aryan Aiyappa, Ms. Anjali Bhardwaj
Country	India
Abstract	SMEs in today’s increasingly competitive business world must know, in real-time, what customers genuinely value and respond accordingly. However, conventional methods of quantifying Customer Perceived Value have utilized surveys and historical data, which are slow, subjective, and unable to access real-time customer sentiment. It is proposed that this paper create a real-time framework that combines the Internet of Things and Explainable Artificial Intelligence to predict and explain CPV at any time. The use of RFID tags and production sensors will enable IoT devices to capture data on customer–product interactions. This analysis, combined with artificially intelligent software that renders inferences about the data, will allow a Random Forest model to forecast CPV. In this instance, artificially intelligent forecasts will not be black-boxed. Instead, I utilize the SHAP and LIME techniques to render each forecast comprehensible. The predictive model and the customers update the forecast, and one can understand what causes a high or low-perceived value at any given moment. Thus, the framework will offer feedback. That is, extraction from the explanation process has the potential to affect change. These insights guide the collection of managerial activities that will drive adjustments in customer behaviors and thus their forecast. This integrated use of the IoT and XAI not only improves prediction accuracy but also establishes managerial confidence, resulting in decentralized, data-driven decision-making. SMEs can subsequently take that technique and become responsive to proactive action, enhancing overall transparency and real-time analytics.
Keywords	Internet of Things (IoT), Explainable Artificial Intelligence (XAI), Customer Perceived Value (CPV), Small and Medium-sized Enterprises (SMEs), Machine Learning (ML), Real-time Analytics, SHAP, LIME, Predictive Modeling, Transparent Decision-Making, Customer Behavior, Value Co-Creation.
Field	Computer Applications
Published In	Volume 7, Issue 5, September-October 2025
Published On	2025-10-31
DOI	https://doi.org/10.36948/ijfmr.2025.v07i05.59281

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Real-time Decision System Customer Perceived Value (Cpv) Via Internet of Things (Iot) and Explainable Ai (Xai)

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