EVision: An AI-Driven, Machine Learning and Data Analytics Enhanced Personalized Electric Vehicle Recommendation Framework of Carbon Negative Concrete Using Algae Derived Additives

EVision: An AI-Driven, Machine Learning and Data Analytics Enhanced Personalized Electric Vehicle Recommendation Framework. Now that the global electric vehicle market is gaining momentum, personalized recommendations are even more crucial to meet varied consumer needs and guide them toward decisions. Based on this crucial need, this paper introduces EVision: new recommendation platform that takes advantage of machine learning, data analysis, and artificial intelligence to present well-personalized EV vehicle suggestions. Overcomes All Limitations Compared to Traditional Recommendation Systems. Such a system combined a recommendation engine, data analytics for understanding real consumer needs, and an NLP-based chatbot [1], [2]. The framework thus contributes to a sustainable ecosystem of EV and aims to support the increased participation of users and decision-making. Experimental results demonstrate that EVision is effective at boosting the accuracy of suggestions and improving user satisfaction with excellent potential for future adoption of EV

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-11-08
DOI
https://doi.org/10.5281/zenodo.17556603
Primary Topic
Electric Vehicles and Infrastructure
Type
article
Field-Weighted Citation Impact
0.00
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article

EVision: An AI-Driven, Machine Learning and Data Analytics Enhanced Personalized Electric Vehicle Recommendation Framework of Carbon Negative Concrete Using Algae Derived Additives

Zenodo (CERN European Organization for Nuclear Research)
Electric Vehicles and Infrastructure
article

EVision: An AI-Driven, Machine Learning and Data Analytics Enhanced Personalized Electric Vehicle Recommendation Framework of Carbon Negative Concrete Using Algae Derived Additives

article en

Abstract

EVision: An AI-Driven, Machine Learning and Data Analytics Enhanced Personalized Electric Vehicle Recommendation Framework. Now that the global electric vehicle market is gaining momentum, personalized recommendations are even more crucial to meet varied consumer needs and guide them toward decisions. Based on this crucial need, this paper introduces EVision: new recommendation platform that takes advantage of machine learning, data analysis, and artificial intelligence to present well-personalized EV vehicle suggestions. Overcomes All Limitations Compared to Traditional Recommendation Systems. Such a system combined a recommendation engine, data analytics for understanding real consumer needs, and an NLP-based chatbot [1], [2]. The framework thus contributes to a sustainable ecosystem of EV and aims to support the increased participation of users and decision-making. Experimental results demonstrate that EVision is effective at boosting the accuracy of suggestions and improving user satisfaction with excellent potential for future adoption of EV

Zenodo (CERN European Organization for Nuclear Research)
Life in Land, Responsible consumption and production
Openalex Percentile: Top 48%
Electric Vehicles and Infrastructure
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EVision: An AI-Driven, Machine Learning and Data Analytics Enhanced Personalized Electric Vehicle Recommendation Framework of Carbon Negative Concrete Using Algae Derived Additives · Zenodo (CERN European Organization for Nuclear Research) (2025) | TGRS Research Map | TGRS