Revolutionizing Home-Office Call Centers: Object Recognition for Performance and Data Security

Modern call centers operate within complex ecosystems where digitalization, automation, and surveillance technologies intersect. These advancements enable multi-channel communication, personalized services, and proactive customer support. Moving beyond traditional phone-based models, modern call centers leverage digital tools to enhance operational efficiency and customer experience. One of the key technologies driving this transformation is image processing techniques. These technologies automate tasks, minimizing human intervention and optimizing workflow. With the rise of home-office work setups, physical workspaces have become less common, and the boundaries between work and personal life have blurred. This situation causes employees to feel less supervised, leading to inefficient use of work hours and potential data breaches. This project aims to protect home-office employees' performance and data security using image processing technology, specifically object recognition and detection methods. The goal is to prevent issues such as virtual idleness, unauthorized data recording, and behaviors against workplace culture without violating employee privacy. By detecting objects such as phones, pens, paper, cameras, tablets, and cameras, behaviors that don't align with company culture will be prevented, and data privacy violations will be avoided. The proposed system demonstrates high performance, with object recognition algorithms achieving approximately 90% accuracy.