## 3 Materials and Methods
Data are sent in a stream of bits. The Arduino IDE provides a serial monitor for debugging and displaying data sent or received via serial communication. The Arduino mega controller is connected to a PTCL Wi-Fi router using an Ethernet shield. This enables wireless transmission of data to the receiving and management unit, which is a user-friendly MATLAB GUI that displays real-time sensor data, and users can interact with the system through this interface. The captured data from sensors is then transmitted to the monitoring unit, where it is retrieved and prepared for further processing. Before the data can be analyzed, it undergoes signal conditioning to enhance its quality and reliability. This involves amplification, filtering, and other preprocessing techniques to improve the signal-to-noise ratio and remove any interference. The conditioned data are then converted from analog to digital format using analog-to-digital converters (ADCs). This digital representation of the sensor readings is more suitable for processing and analysis. The processed data are integrated and analyzed to extract meaningful insights. This stage involves applying algorithms and statistical techniques to interpret the data and identify patterns or anomalies. Customized algorithms are developed to analyze the sensor data and extract relevant information. These algorithms are designed to detect deviations from normal operating conditions, predict equipment failures, or optimize process parameters. The developed algorithms are implemented in MATLAB and run on the monitoring unit. The graphical user interface (GUI) developed using MATLAB R2020a provides a user-friendly platform for visualizing real-time sensor data and making informed decisions. It presents the data in a comprehensible format and allows users to interact with the system. These programs process the incoming sensor data in real time and generate actionable insights or alerts. The processed data are transmitted wirelessly to the receiving and management unit for further analysis and decision-making. Wireless communication enables seamless data transfer and remote monitoring capabilities. This unit serves as the central hub for data aggregation, storage, and analysis. It receives the processed sensor data from multiple sources and manages them through a centralized system. These components facilitate network connectivity and enable data transfer between the monitoring unit and other devices in the system. Ethernet shields provide wired connectivity, while PTCL Wi-Fi routers enable wireless communication. The processed sensor data are displayed in real-time on the MATLAB GUI, allowing users to monitor the status of various parameters and take immediate action if necessary. Based on the information displayed on the GUI, users can make informed decisions regarding process optimization, equipment maintenance, or other relevant actions. This feedback loop enables continuous improvement and proactive management of the textile manufacturing process. The workings of the methodology are further divided into three parts, allowing for a comprehensive examination of the real-time monitoring process in the textile sector. * Transmitting side
* Receiving side
* Graphical user interface (GUI)  
The components used in this research consist of sensors designed to measure various physical parameters within the textile manufacturing environment. These sensors are strategically placed throughout the facility to capture real-time data on environmental conditions. The revolutionary system shown in Figure 4 is specifically applied to Pakistan's textile industry due to its ability to address unique challenges such as high production costs, inefficiencies, and outdated technology, as well as mitigating localized issues like unreliable power supply and limited access to advanced technology through IoT solutions.