People Flow Statistics - SenseCraft_Rick - CodeCraft Hub

Documentation

1. Application Introduction This application achieves in-depth integration between the reCamera series of smart cameras and Node-RED, converting edge AI visual detection capabilities into standard IoT signals to address the pain point of traditional surveillance – “only visible, unable to link and execute”. With virtual red lines as the core control tool, it accurately divides Area A and Area B, counts the number of targets staying in each area in real time, analyzes cross-boundary two-way traffic and movement trajectories, and supports one-click switching of detection targets. It completely replaces manual inspections and builds a full-domain visual management system. 2. Scenario Applications ● Smart Retail : Deploy virtual red lines at store entrances and cashier areas to accurately calculate store entry rate and purchase conversion rate, quantify the effectiveness of marketing campaigns, and help optimize store operation strategies and passenger flow management. ● Smart Security : Set up virtual red lines at perimeters, sentry entrances and exits, and restricted areas to filter false alarms triggered by small animals and light changes. It realizes off-duty monitoring and illegal intrusion control, enabling unattended security management and reducing labor costs. ● Smart Transportation : Install virtual red lines at crosswalks to count the crossing traffic of pedestrians and non-motor vehicles, providing reliable data support for intersection signal timing optimization and road renovation and upgrading. ● Industrial Warehousing : Lay virtual red lines along forklift and cargo circulation routes to monitor unauthorized intrusions into restricted areas, standardize cargo circulation procedures, ensure safe operation in the factory area, and improve warehousing operation efficiency. 3. Core Technologies and Advantages ● Efficient Edge AI Processing : Driven by the SenseCraft engine, all visual analysis is completed at the device end, outputting lightweight structured data without transmitting high-definition video streams, ensuring stable system operation. ● Privacy Security + Local Deployment : The entire system operates in a closed loop within the local area network, and video and biometric data are not uploaded to the cloud, completely eliminating the risk of data leakage. 4. Software and Hardware Preparation 4.1 Hardware Carrier ● reCamera Artificial Intelligence Camera (core visual acquisition terminal) reCamera 2002w 8GB-Open Source AI Camera for YOLO at the Edge 4.2 Software Platform ● SenseCraft : Responsible for application distribution, AI model loading and management ● Node-RED : Undertakes data processing, linkage logic orchestration and data preview display

1. Application Introduction This application achieves in-depth integration between the reCamera series of smart cameras and Node-RED, converting edge AI visual detection capabilities into standard IoT signals to address the pain point of traditional surveillance – “only visible, unable to link and execute”. With virtual red lines as the core control tool, it accurately divides Area A and Area B, counts the number of targets staying in each area in real time, analyzes cross-boundary two-way traffic and movement trajectories, and supports one-click switching of detection targets. It completely replaces manual inspections and builds a full-domain visual management system. 2. Scenario Applications ● Smart Retail : Deploy virtual red lines at store entrances and cashier areas to accurately calculate store entry rate and purchase conversion rate, quantify the effectiveness of marketing campaigns, and help optimize store operation strategies and passenger flow management. ● Smart Security : Set up virtual red lines at perimeters, sentry entrances and exits, and restricted areas to filter false alarms triggered by small animals and light changes.