AI For smart Surveillance and Anomaly Detection
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| Format: | Recurso digital |
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2025
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| _version_ | 1866902076106211328 |
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| author | Pawan Sen Digvijay Singh Rathore Aradhya Gupta |
| author_facet | Pawan Sen Digvijay Singh Rathore Aradhya Gupta |
| contents | <p>Abstract<br>As customer service rapidly evolves in the digital era, businesses are increasingly deploying chatbots to manage user<br>interactions, aiming to reduce costs, increase efficiency, and provide instant support. At the same time, human agents<br>continue to play a vital role in delivering personalized, empathetic, and adaptive communication. This research paper<br>presents a comparative study of chatbots and human agents, examining their respective strengths and limitations across<br>key factors such as response time, emotional intelligence, scalability, cost-effectiveness, problem-solving capability, and<br>customer satisfaction. Drawing on real-world implementations, user behavior analysis, and industry practices, the study<br>reveals that while chatbots offer superior speed, availability, and consistency, they struggle with complex queries and<br>emotional nuance—areas where human agents excel. The paper argues that the most effective customer service models<br>are hybrid systems that leverage the efficiency of AI-powered chatbots alongside the emotional intelligence and<br>adaptability of human support. As AI technologies continue to advance, understanding the appropriate use cases for<br>automation versus human interaction becomes crucial for businesses seeking to enhance customer experience while<br>maintaining operational efficiency.</p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_15443347 |
| institution | Zenodo |
| language | |
| publishDate | 2025 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | AI For smart Surveillance and Anomaly Detection Pawan Sen Digvijay Singh Rathore Aradhya Gupta <p>Abstract<br>As customer service rapidly evolves in the digital era, businesses are increasingly deploying chatbots to manage user<br>interactions, aiming to reduce costs, increase efficiency, and provide instant support. At the same time, human agents<br>continue to play a vital role in delivering personalized, empathetic, and adaptive communication. This research paper<br>presents a comparative study of chatbots and human agents, examining their respective strengths and limitations across<br>key factors such as response time, emotional intelligence, scalability, cost-effectiveness, problem-solving capability, and<br>customer satisfaction. Drawing on real-world implementations, user behavior analysis, and industry practices, the study<br>reveals that while chatbots offer superior speed, availability, and consistency, they struggle with complex queries and<br>emotional nuance—areas where human agents excel. The paper argues that the most effective customer service models<br>are hybrid systems that leverage the efficiency of AI-powered chatbots alongside the emotional intelligence and<br>adaptability of human support. As AI technologies continue to advance, understanding the appropriate use cases for<br>automation versus human interaction becomes crucial for businesses seeking to enhance customer experience while<br>maintaining operational efficiency.</p> |
| title | AI For smart Surveillance and Anomaly Detection |
| url | https://doi.org/10.5281/zenodo.15443347 |