## 4 Results and Discussion
### Transformer Condition Monitoring
#### 4.8.4 Partial Discharges  
Partial discharge (PD) is a leading cause of transformer deterioration and failure. PD happens when electrical stress surpasses the transformer's insulation resilience, resulting in tiny sparks or arcs that damage the insulation and impair the transformer's reliability [33]. Partial discharges are commonly defined as minor electrical sparks that are generated in the windings of the transformer [20]. This phenomenon takes place when there are small air gaps in or within the insulation. When the sparking happens, the transformer windings begin to degrade. The wider the void in insulation, the larger the probable discharge, which could potentially contribute to equipment breakdown. Partial discharge analysis and monitoring is a strong predictor of possible transformer failure. If kept undiagnosed, it may ultimately result to a total breakdown of the electrical insulation, which serves as one of the leading causes of transformer unplanned outages. Partial discharge analysis and monitoring is a strong predictor of possible transformer failure. If kept undiagnosed, it may ultimately result in total breakdown of the electrical insulation, which serves as one of the leading causes of unplanned outages in transformers. Utilizing online monitoring systems such as the IoT to gather real-time data and detect partial discharges can help prevent transformer failures. The following condition monitoring techniques for partial discharges was proposed by [20]. Dissolve gas analysis (DGA) is one technique that can be utilized to monitor the concentration of dissolved gasses in the transformer oil. A DGA can reveal significant levels of thermal gasses in transformer oil such as methane, ethane, and ethylene as an indication of transformer oil overheating. These gasses are produced because of transformer oil thermal degradation. DGA forms part of the predictive maintenance strategy that can be utilized to monitor incipient faults and take reasonable action before transformer failure occurs [20]. There are IoT sensors available in the market that can facilitate real-time data gathering of the concentration of these gasses. Gas sensors such as the HKD MQ7 gas sensor module monitors carbon monoxide (CO), and the MQ-4 Methane gas sensor, etc., are readily available in the markets. IR sensors such as the IR Infrared obstacle avoidance sensor module are available in the market to monitor hot spots due to partial discharges in the transformer. To ascertain responses to the eight main research questions formulated in Section 1, this current SLR examines a total of 120 research works about IoT technology in transformer condition monitoring that were conducted from 2014 to 2024. RQ1: What are the primary research objectives and goals addressed in the collected literature on IoT technology for electrical transformer condition monitoring and fault diagnosis? The results of the literature study conducted for this paper provide a comprehensive overview of research articles relevant to the application of Internet of Things technology in electrical transformer condition monitoring, as shown in Figure 10. Fault diagnosis is the most notable of the highlighted research fields in terms of primary focus. The application of advanced modeling and monitoring techniques for the diagnosis and identification of problems in transformers has been the subject of 45.8% publications in total. Moreover, 24.2% of the studies examined the development and use of health indices to assess the overall well-being of transformers using an IoT infrastructure. Transformer lifecycle management is another important component. To optimize transformer lifespan, 22.5% of researchersused Internet of Things technology to study this topic. The analysis also highlights 1.7% of vibration monitoring research and 4.2% of studies that optimize transformer energy usage. There was no partial discharge identification or thermal performance analysis in any of the literature that was gathered.