## 2 Literature Review
### IoT Technologies for Roadside Surveillance  
Following recent advances in technology, roadside surveillance is not only based on cameras but also on other emerging technologies, aimed at achieving various aims and objectives. Researchers have been most interested in the development and applications of radio tomographic imaging (RTI), wireless sensor networks (WSNs) and computer vision for roadside surveillance. Radio tomographic imaging is an emerging technology that localizes and tracks moving physical objects in an area surrounded by simple and inexpensive radios in wireless networks [17]. The concept of RTI originates from radar systems. Using concepts from radar, RTI originally worked by placing small and inexpensive radios around the area of interest. The radios were able to transmit and receive wireless signals, creating a dense network of links passing through the area. If an object moved within the area, it would reflect or absorb the wireless signal and prevent some of the power from reaching its destination. Hence, an image could be formed of where the power was being absorbed, by utilizing the link's power-loss measurements. Therefore, it could indicate the locations of any detected and tracked objects. More recently, RTI has been proposed for tracking the location of objects via radio waves, without requiring objects to transmit or receive radio signals. This occurs when the position is extracted by inferring which voxels are obstructing a subset of radio links in a dense wireless sensor network [18]. [PERSON] et al. [19] demonstrated a novel application of RTI with a secure wireless sensor network for roadside surveillance and vehicle identification and tracking, by combining frames of a moving vehicle into a single image using a vehicle class-identification algorithm. However, the technology of RTI is subject to the speed at which it can detect objects moving through the network [2]. Speed is limited by the time it takes to perform a single scan of the network area. Vehicles on roads are not always static. If some vehicles are travelling at high speeds which are out of the system specification range, RTI might not record anything, thus affecting the process of measuring traffic parameters. Thus, RTI is not totally suitable for all-round roadside surveillance; only for object detection and tracking at relatively low speeds. WSNs use networked microsensor technology, which is one of the most important technologies of the 21 st century and a key technology for the future [20]. Wireless sensor networks offer an attractive, low-cost alternative to inductive loops, video and radar, for traffic surveillance on freeways, at intersections and in car parks. According to [PERSON] et al. [21], these networks typically consist of a set of sensor nodes comprising a sensor, a microprocessor, a radio, a battery and an access point, together with a radio and a more powerful processor. The sensor nodes are utilized to process real-time measurements and transmit useful data to the access point located at the roadside, through direct communication via either line or solar power. This then enables the detection of vehicles and the estimation of various traffic parameters. [PERSON] and [PERSON] [22] utilized a network of small sensor nodes, communicating wirelessly among themselves, to sense the physical world. After the collection of data from the detection events using the sensor nodes, the access point could calculate the number, occupancy and speed of monitored traffic. It is evident, therefore, that WSNs offer an attractive, low-cost alternative to inductive loops, video and radar, for traffic surveillance. However, [PERSON] et al. [23] have argued that WSNs are easily affected by their surroundings, e.g., by walls, microwaves or signal attenuation due to large distances. These networks also have a comparatively low speed of communication with the server and are easily disrupted by elements such as Bluetooth.