Abstract: This paper details the development and Python implementation of a cost-effective Real-Time Face Recognition Remote Monitoring Attendance System, specifically designed for deployment in small industries and micro-enterprises operating on limited budgets. Addressing the shortcomings of traditional manual attendance methods, this system leverages computer vision to provide an automated, contactless solution. Utilizing readily available hardware such as a standard laptop and webcam, the system employs Python libraries like OpenCV for real-time video stream processing and face recognition libraries (e.g., face_recognition) for accurate identification against a registered employee database. Upon successful recognition of an individual, their attendance, along with a timestamp, is automatically logged directly into an Excel spreadsheet. A key feature is the remote monitoring capability, enabled through a simple web interface (potentially built with Flask or Django), allowing administrators to access attendance logs and manage the system remotely. To further enhance usability, the system automatically compiles the daily attendance records from the Excel sheet and emails the report to designated personnel (e.g., supervisors or faculty). This Python-based implementation offers a practical, rapidly deployable, and highly useful application, providing small organizations with an affordable, efficient, and accurate method for attendance management while eliminating proxy attendance and enabling convenient remote oversight.