## 2 Literature Review
### The Internet of Things: A Review
[63] stated that a transformer is designed to operate between 20 and 25 years. However, its dependability becomes impacted by overloading, heating, low or high voltages and currents, or both. In these cases, it will experience abrupt failure, and many users will lose power. Overloading, insulation failure, and insufficient transformer cooling are the primary causes of distribution transformer failure. Most of the papers reviewed in this paper proposed IoT systems to address issues associated with overloading, oil temperature, load current, voltage, and oil level. The extensive dispersion of transformers in today's electric networks makes it difficult to manually evaluate each one's condition; hence, researchers are delving more into the IoT-based transformer condition monitoring approach for timely fault detection and condition monitoring of transformers. The papers collected for this review indicated that there are layers of technologies, protocols, and standards required for IoT-based transformer condition monitoring architecture to establish successful IoT communication. These layers are crucial in assisting the IoT-based transformer condition monitoring devices to communicate with each other and enable scalability, heterogeneity, and interoperability [63]. The level of layers differs as required by that application. [64] stated that there are various layers, namely, three layers, four layers, five layers and OSI layers in IoT systems, with OSI being a seven-layer system. The papers considered for this review adopted a three-layer approach where there was a top layer, middle layer, and bottom layer. The top layer is mainly employed for the user functions requirement, the middle layer is utilized for the network functions requirement, and the bottom layer is designated for the hardware functions requirement [65]. The top layer is also known as the service data layer for data storage and visualization; in simple terms, this is a cloud IoT platform where the transformer's monitored data are being monitored and stored. The middle layer falls under network and communication and includes the network layer [65], transport layer [66], and middleware layer [67] or Internet layer [68]. This layer oversees connections to other smart devices and network nodes, such as IoT clouds, gateways, servers, and routers. It offers a variety of services to both the lower and upper layers. This layer manages the transmission of sensor data via networks such as Wi-Fi, Bluetooth, ZigBee, GSM, radio frequency identification (RFID), LAN, WAN, GPRS LTE, etc. It also controls data packet routing and processing. The most used method of communication for IoT-based transformer condition monitoring was Wi-Fi due to many projects' experiments conducted in controlled areas and distance being a major constraint. The bottom layer is referred to as the sensing layer [69]. This layer connects the physical sensing devices to the digital world, allowing for machine-to-machine communication. The sensors on this layer detect and collect data, including physical properties of the transformer such as the load current, voltage, transformer temperature, and oil level. The sensors can measure the humidity, pressure, temperature, voltage, current and level. The value of the measured parameters is converted into signals and machine languages that can be transmitted and received. The papers mostly used IoT technology to measure load current, voltage, temperature, and oil level. Other papers utilized these data to estimate the health index and conduct fault diagnosis in the transformer. Figure 1: A typical diagram of the Internet of Things [5].