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@article{207662,
        author = {Onkar Balaji Gawali and Jeevan Eshavar band and Sarthak Satish Phalke and Sahil Navnath Phalke and Naitik Soni and Devakinandan Shete},
        title = {IoT-Based Smart City Framework: An Integrated Seven-Module Approach Using Arduino UNO for Urban Automation and Resource Management},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {13},
        number = {3},
        pages = {1961-1969},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=207662},
        abstract = {Rapid urbanization has placed increasing strain on civic infrastructure, producing traffic congestion, uncontrolled energy consumption, water wastage, rising air pollution, and inefficient parking utilization. Conventional municipal systems rely heavily on fixed timers and manual supervision, which cannot adapt to real-time urban conditions. This paper proposes an integrated Smart City Framework built entirely around low-cost Arduino UNO microcontrollers that unifies seven independent automation modules smart home automation, smart traffic signal control, smart irrigation, smart weather/air-quality monitoring, smart parking management, vehicle speed detection, and smart street lighting into a single, modular urban automation testbed. The problem addressed is the absence of a low-cost, easily replicable prototype that demonstrates how sensor-actuator automation can simultaneously target energy optimization, water conservation, dynamic traffic flow, environmental monitoring, safe parking allocation, and public-safety enforcement without dependence on expensive SCADA or proprietary smart-city platforms.
The proposed system follows a layered sensor–controller–actuator architecture. Each module uses passive infrared (PIR), infrared (IR), soil-moisture, rain, MQ135 gas, DHT11, and light-dependent-resistor (LDR) sensors interfaced to Arduino UNO boards, which drive relays, servo motors, and LED/LCD outputs to automate physical responses without human intervention. Embedded C++ firmware developed in the Arduino IDE governs decision logic for each subsystem, and a 16x2 LCD provides local telemetry. Bench-level testing of all seven modules confirmed reliable operation: motion-triggered lighting and rain-triggered shed protection responded within sub-second latency, traffic-queue override reduced simulated red-light wait time, soil-moisture-triggered irrigation prevented both under- and over-watering, the weather station reported gas, humidity, and rainfall data reliably on the LCD, the parking module correctly tracked slot occupancy and gated entry, the speed detector computed vehicle velocity from a fixed IR baseline with acceptable accuracy, and the streetlight circuit switched autonomously with ambient light level. The prototype demonstrates that a fully integrated, low-cost, modular smart-city testbed is achievable using commodity Arduino hardware, offering a scalable educational and pre-deployment reference architecture. Future work outlined in this paper extends the system toward cloud/MQTT connectivity, mobile-app monitoring, AI-based traffic prediction, edge computing, solar-powered operation, and V2I communication for full-scale municipal deployment.},
        keywords = {Smart City; Internet of Things; Arduino UNO; Smart Traffic; Home Automation; Smart Irrigation; Smart Parking; Weather Monitoring; Embedded Systems.},
        month = {August},
        }