Ensuring security is the major concern in this modern era in order to lead a healthy relaxed life. In many commercial and non-commercial sectors, people counting and surveillance are important for ensuring security. The number of people entering and leaving important places like business establishments, shops or shopping malls, office buildings, server rooms, or data centers has become essential for security officers or operators to have useful information at the right time. Nowadays, CCTV-based security systems are widely used, which do not send real-time alert notifications to the authorities after any untoward incident occurs unless a security team monitors the system 24/7. The emergence of Industry 4.0 in the current economic trend promotes the usage of Artificial Intelligence (AI) in service development. Computer Vision has played a major role in the image processing and traffic surveillance sector. This study aims to design and implement a cost-effective IoT-based smart Human Traffic Monitoring (HTM) system capable of detecting authorized and unauthorized people as well as storing relevant information. One of this research’s major concerns is creating the functionality to notify the authority in real-time and the ability to interact with the system remotely. To accomplish our desired goal, we use a low-cost Raspberry Pi machine for processing and transmitting data, a PIR sensor for detecting motions, and a Pi camera for capturing images.