The integration of physical security systems with environmental safety monitoring represents a critical advancement in smart infrastructure management. Traditional approaches maintain these systems as independent silos, creating operational inefficiencies, delayed emergency responses, and increased management complexity. This paper presents a comprehensive dual-modality Internet of Things framework that seamlessly integrates RFID-based access control with multi-sensor environmental safety monitoring through a unified cloud architecture. The system comprises two coordinated subsystems: Subsystem 1 implements RFID authentication with servo-actuated gate control and real-time Google Sheets logging, while Subsystem 2 provides comprehensive safety monitoring incorporating flame detection, water flow measurement, LCD status display, and personnel identification. Both subsystems utilize ESP32 microcontrollers for edge processing and wireless connectivity. Experimental evaluation over 45 days demonstrates exceptional performance metrics: 99.2\% RFID authentication accuracy with 0.82-second average response time, 98.5\% flame detection reliability within 5-meter range, and 99.8\% cloud data logging success rate. The system maintains operational integrity during network disruptions through intelligent local caching mechanisms and achieves total implementation cost of 5,400 BDT (approximately \$48), representing an 82\% reduction compared to commercial integrated solutions. This research establishes a practical framework for synergistic security-safety integration, demonstrating that professional-grade performance can be achieved through careful architectural design and component optimization while maintaining exceptional cost-effectiveness and accessibility for diverse application scenarios.

翻译：物理安防系统与环境安全监测的集成代表了智能基础设施管理领域的关键进展。传统方法将这些系统作为独立的孤岛进行维护，导致运行效率低下、应急响应延迟以及管理复杂性增加。本文提出了一种全面的双模态物联网框架，该框架通过统一的云架构，将基于RFID的门禁系统与多传感器环境安全监测无缝集成。该系统包含两个协调的子系统：子系统1实现了RFID认证与伺服驱动门控，并具备实时Google Sheets日志记录功能；子系统2则提供全面的安全监测，包括火焰检测、水流测量、LCD状态显示及人员识别。两个子系统均采用ESP32微控制器进行边缘处理和无线连接。为期45天的实验评估展示了卓越的性能指标：RFID认证准确率达99.2%，平均响应时间为0.82秒；火焰检测在5米范围内可靠性达98.5%；云端数据记录成功率达99.8%。该系统通过智能本地缓存机制在网络中断期间保持运行完整性，总实现成本为5400孟加拉塔卡（约合48美元），相比商业集成解决方案降低了82%。本研究建立了一个用于协同安防-安全集成的实用框架，证明通过精心的架构设计和组件优化，可以在保持卓越成本效益和广泛适用性的同时，实现专业级的性能。