Determination of Crosstalks using Mems

Mr. E Satheesh Kumar

 Department of Electronics and Communication Engineering Annamacharya Institute of Technology and SciencesTirupati,India

esatheesh79@gmail.com

Shaik Khaja Nayab Rasool

Department of Electronics and Communication EngineeringAnnamacharya Institute of Technologyand Sciences Tirupati,India

khajanayabrasoolshaik750@gmail.com

Sanappireddy Karthik Kumar Reddy

Department of Electronics and Communication EngineeringAnnamacharya Institute of Technology and Sciences Tirupati,India

sanapureddykarthik192@gmail.com

Chinthagumppala Lohitha

 Department of Electronics and Communication Engineering Annamacharya Institute of Technology and Sciences

Tirupati,India chinthagumpalalohitha@gmail.com

Syed Muhammad Ilyas

 Department of Electronics and Communication Engineering Annamacharya Institute of Technology  and SciencesTirupati,India

syedilyas4403@gmail.com

Abstract: Micro-Electro-Mechanical Systems (MEMS) accelerometers are extensively employed in motion sensing and embedded monitoring applications. However, the performance of these sensors can be influenced by cross-axis interference, commonly referred to as cross-talk, which affects the accuracy of acceleration measurements. This paper presents the design and implementation of a real-time cross-talk detection and analysis system using a three-axis MEMS accelerometer interfaced with an Arduino Uno microcontroller. The system utilizes the MPU-6050 sensor to capture acceleration data along the X, Y, and Z axes. The collected signals are analyzed using cross-correlation techniques to evaluate the level of interference between orthogonal sensing axes and to identify unintended signal coupling. Such cross-axis effects can introduce significant errors in applications such as robotics, wearable devices, structural health monitoring, and inertial navigation systems. To enable remote data access and real-time monitoring, a NodeMCU ESP8266 module is integrated to transmit sensor data to a cloud-based visualization platform. The acceleration data is continuously processed and displayed through graphical representations, allowing users to observe axis interactions and signal dependencies in real time. Experimental results demonstrate that the proposed system effectively identifies cross-axis interference while maintaining a low-cost hardware configuration with scalable IoT connectivity. The developed approach provides a practical framework for enhancing the reliability and accuracy of MEMS-based motion sensing systems.Keywords— MEMS accelerometer, Cross-axis interference, Cross-talk detection, Motion sensing, Arduino Uno, MPU-6050 sensor, Internet of Things (IoT), NodeMCU ESP8266, Cross-correlation analysis, Real-time monitoring, Embedded systems, Wireless sensor networks