In recent years, large quantities of illegal TV Box equipment have been confiscated in Brazil. According to news released in March 2024, an estimated 2.5 million TV Boxes were stored in the warehouses of the Federal Revenue Service. Typically, this equipment is destroyed, which not only incurs significant costs for the government but also generates substantial e-waste. Meanwhile, the advancement of smart city applications based on the Internet of Things (IoT) and machine learning has driven research in edge computing using hardware-constrained devices. This paper explores the feasibility of repurposing TV Boxes for edge computing in applications involving people counting in images collected by cameras. We developed a testbed consisting of 20 TV boxes to conduct a thorough evaluation of their resilience and carbon footprint compared to commonly used edge computing equipment. Our findings demonstrate that these repurposed devices can perform over five million inferences, outperforming commercially available devices in terms of carbon footprint using Brazilian energy matrix. This study underscores the innovative potential and environmental benefits of repurposing TV Boxes for smart city applications, especially when utilizing lightweight machine learning models.