<![CDATA[The rapid growth of Internet of Things (IoT) technology has motivated numerous studies to develop motion-based security systems that combine Passive Infrared (PIR) sensors with microcontrollers and instant-messaging platforms such as Telegram. A review of four recent studies on PIR-based IoT motion detection, however, shows that each system still carries partial limitations: some provide visual verification through a camera module but lack an offline data-retention mechanism, while others record activity to a cloud platform but do not capture images, leaving alerts without visual evidence. This study aims to synthesize the strengths and shortcomings of the four reviewed systems through a comparative literature analysis and to propose a refined system architecture that consolidates their complementary features while resolving their respective gaps. The research applies a descriptive-qualitative literature review combined with a design-science approach to formulate an enhanced architecture consisting of a PIR sensor, an ESP32-CAM module, a Telegram Bot API for dual text-and-image alerts, cloud-based data logging on ThingSpeak, and a local offline-backup mechanism using SPIFFS, supplemented with an adaptive debounce filter to reduce false triggers. The outcome of this study is a conceptual architecture, block diagram, and operational flowchart that integrate visual verification, persistent logging, and connectivity resilience within a single design, providing a more complete reference for future implementation of IoT-based motion detection security systems.]]>
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