# IoT-Based Smart Surveillance System for High-Security Areas
## 1 Introduction
### State of the Art
Ultimately, the optimal model is determined using the BIC method. The obtained results validate the effectiveness of our prediction models, as they consistently outperform all other mentioned prediction models across all evaluation metrics. Based on the experimental results obtained from the CoMon project dataset, it has been observed that the proposed approach consistently achieves superior accuracy when compared to other ensemble prediction algorithms. These findings highlight the effectiveness and competitiveness of our approach in accurately predicting outcomes and outperforming alternative methods within the context of the CoMon project [27]. The domain of through-wall radar imaging and detection is witnessing substantial growth, but a major challenge lies in dealing with strong clutter that often masks a target's presence, thereby hampering accurate detection. In this research paper, a novel algorithm is introduced to address clutter reduction and target downrange correction in through-wall monostatic radar imaging. The algorithm involves organizing the received radar signals into a matrix and subsequently dividing this matrix into frames for further processing [28]. The Doppler method is often combined with other techniques that are helpful to determine the presence of living things; therefore, it is used in medical fields and rescue operations where debris has buried humans during an earthquake, explosion, or other disaster. Therefore, it is not suitable for a security framework due to its complexity. To overcome the above-discussed issues, low-cost devices that work on microwave signals are helpful from the human perspective with respect to seeing moving or suspected objects behind obstructions. These low-cost devices can be used to revolutionize human life in terms of, e.g., home automation, gaming, healthcare, rescue services, and law enforcement. In the above-mentioned areas, low-cost devices play a vital role in assessing any level of threat behind a wall in hostage situations or rescue missions. SS-HSA focuses on issues related to homeland or personal security from theft, larceny, burglary, and illegal activities performed in or near houses. For this purpose, GMS is selected because Infrared sensor (IR) ultrasound sensor radar module thermal cameras and localization sensors are affected by adverse weather conditions such as heavy rain, fog, dust, snow, and temperature fluctuations, whereas GMS is not affected in such scenarios. GMS technology has emerged as the preferred choice for many applications. It has a strong penetrative ability and range resolution capacity with respect to obstructions. It has a detection distance from 2 to 16 m and a continuously adjustable range resolution that helps to differentiate multiple objects. GMS operates at a baseband up to 10.525 GHz, granting it a strong capacity not only for penetrating nonmetallic walls but also detecting a suspected object behind a wall. In this way, using GMS, in conjunction with Arduino UNO and GSM, is helpful for taking proactive measures in real-time to prevent crimes such as thefts, robbery, burglary, and other occurring in houses. Arduino UNO is an open-source microcontroller board. A schematic of the proposed SS-HSA is shown in Figure 2.