This literature review synthesizes findings from 20 studies that explore earthquake detection systems using low-cost accelerometer-based sensors integrated with microcontrollers, such as Arduino, and other IoT technologies. The comparative analysis focuses on sensor selection, sensitivity, noise levels, and system efficacy across various implementations. The ADXL355, LIS3DHH, MPU6050, and ADXL345 accelerometers emerged as commonly tested sensors, each demonstrating unique strengths in seismic activity monitoring. Studies highlight the ADXL355 and LIS3DHH for their low noise and high sensitivity, making them preferred for detecting subtle ground movements, while the MPU6050’s six-axis functionality offers versatility in multi-dimensional motion analysis. Additionally, research underscores the importance of accurate calibration and noise mitigation techniques to enhance data reliability. The review concludes that low-cost accelerometers, particularly when combined with IoT frameworks, provide feasible solutions for scalable earthquake early warning systems. However, challenges persist in balancing sensitivity and stability in noisy environments, indicating a need for further refinement in sensor technology and signal processing algorithms to improve detection accuracy and reduce false alarms in real-world applications.