The integration of IoT (Internet of Things) technology in industrial maintenance is transforming machine condition monitoring by enabling real time data acquisition and predictive maintenance. This work presents an IoT-based remote monitoring system for blowers in wastewater treatment plants, utilizing a Total Degradation Number (TDN) sensor for oil condition assessment, existing vibration sensors, and oil temperature monitoring.The system continuously tracks critical blower parameters, including the TDN to evaluate oil degradation, oil temperature, vibration levels, and operational runtime. By applying high-frequency AC waveforms, the TDN sensor accurately measures oil capacitance and conductance, deriving the TDN as a simplified index of oil health. Sensor data is seamlessly collected, transmitted to a cloud platform, and displayed on an intuitive dashboard that provides real-time visualization and automated alerts for abnormal conditions.Field testing in an operational wastewater treatment facility demonstrates the system’s effectiveness in early fault detection, reducing unexpected failures, and optimizing maintenance schedules. The proposed solution enhances equipment reliability, minimizes breakdowns, and extends machine lifespan. Future developments will explore the integration of machine learning algorithms to further refine predictive capabilities and improve overall system performance.

IoT technology is being increasingly adopted in various industries, including manufacturing and agriculture to improve efficiency, productivity, and safety. This paper presents the design and implementation of embedded IoT system applied to fish farms in environmental agency. Dissolved oxygen concentration and temperature in water plays a crucial role in the growth and development of fish. Therefore, it is important to monitor dissolved oxygen concentration and temperature. The system is designed to overcome the limitations of manual monitoring currently used and provide an effective solution for monitoring and control. The proposed IoT system designed and developed from the ground up using commercially off-the-shelf components and open-source software platform for fast, reliable data acquisitions, and data gather by the IoT system get reported to the cloud server in real time. The controller part of the system adjusts the operation of the aeriation pump in real-time, turning it on or off, as needed to maintain the desired dissolved oxygen level without the need for manual intervention, to ensure that the dissolved oxygen level remains within a safe and healthy range for aquatic life. The system also includes a graphical user interface, allowing farmers and investigators to observe, analyse and investigate the related data. As has been proved by practice, the remote data transmission to the cloud combined Radio Frequency techniques for control, is a practical and efficient technology for monitoring the dissolved oxygen in aquaculture, and has greatly increased the safety for the fish in the pond.