AI as Modern Technology for Home Security Systems: A Systematic Literature Review †
Abstract
1. Introduction
2. Research Questions and Motivations
2.1. How Does AI Integration Enhance the Automation and Efficiency of Home Security Systems?
2.2. What Types of AI Technologies Are Commonly Used in Modern Home Security Systems?
2.3. Why Is AI Considered a Transformative Technology for Improving Home Safety and Monitoring?
3. Methodology
4. Results and Discussion
AI as a Modern Technology for Home Security Systems: A Systematic Literature Review
- Real-Time Surveillance and Monitoring: AI-based security systems leverage powerful machine learning and computer vision algorithms to continuously analyze video feeds, detecting unusual activities in real time. This ability to detect abnormalities reduces human oversight and minimizes errors, enabling a more reliable surveillance process. AI systems can instantly alert security personnel or homeowners when suspicious behavior is detected, allowing for quicker responses to potential threats. This form of continuous monitoring is critical in environments where security needs to be active at all times [14].
- Threat Detection and Response: AI-powered systems significantly enhance the ability to detect threats by analyzing patterns and recognizing anomalies that could indicate security breaches. These systems are trained to identify unauthorized access attempts, unusual movements, or other behaviors that could signal a potential danger. Once a threat is identified, AI can trigger automatic responses, such as locking doors, notifying security teams, or activating alarms, ensuring swift action to mitigate risks. By automating the detection and response process, these systems offer a much higher level of protection compared to traditional surveillance methods, which are often reactive and slower in their response times [15].
- A 24/7 Operational Capability: One of the key benefits of AI-based security systems is their ability to operate without interruption. Unlike human personnel who may need rest or breaks, AI systems are capable of maintaining constant vigilance around the clock, ensuring that security measures are always in place. This 24/7 operational capability significantly reduces the likelihood of security lapses due to fatigue or human error, providing peace of mind to homeowners and business owners. The system can continuously monitor for threats, alerting users or responding automatically, ensuring an uninterrupted presence to deter potential intruders at any time of day or night [14].
- Integration with IoT and Smart Systems: AI-based security systems are highly adaptable and can be integrated seamlessly with IoT devices such as cameras, smart locks, motion sensors, and other connected technologies. By leveraging data from various devices, AI can create a cohesive and intelligent security system that responds to changing circumstances. For example, if a motion sensor detects an intruder, the system can trigger cameras to start recording, alert the homeowner, and lock the doors automatically. This integration creates a fully interconnected security ecosystem that enhances the safety and operational efficiency in a smart home environment, providing users with greater control and peace of mind [14].
- Customizable Security Protocols: AI systems can learn and adapt to the specific behaviors, routines, and preferences of homeowners. This adaptability enables the creation of customized security protocols that reflect the unique needs of each household. For example, an AI system can recognize when a homeowner leaves for work and automatically adjust the security settings, such as locking the doors and activating motion sensors. Over time, as the system learns more about the household’s habits, it becomes increasingly effective at predicting and responding to security needs. This level of personalization ensures that security protocols align more closely with individual lifestyles, providing a more tailored and effective security solution [14].
- Cost Efficiency Over Time: While the initial investment in AI-based security systems may be considerable, their long-term benefits often outweigh the costs. By automating surveillance, threat detection, and response, these systems significantly reduce the need for human intervention. This leads to lower operational costs over time, especially when compared to traditional security systems that require constant human monitoring. The reduction in manual labor and the increased accuracy and efficiency of AI-driven systems result in overall cost savings, making them a more sustainable investment for long-term security needs. Moreover, AI systems can scale easily, accommodating growing security needs without the need for substantial additional costs [15].
- Remote Access and Control: One of the standout features of AI-based security systems is the ability for homeowners to remotely monitor and control their security apparatus. Through smartphone apps or web-based interfaces, users can access live video feeds, receive real-time alerts, and even control smart locks or cameras from virtually anywhere. This remote accessibility enhances convenience, allowing homeowners to respond to security events no matter their physical location. For instance, if a user receives an alert about suspicious activity, they can quickly check their cameras and take action—whether that means alerting authorities or activating further security measures. This feature provides flexibility and control, making it easier to manage security from a distance [14].
- Environment Adaptability: AI systems are designed to operate effectively in a wide range of environmental conditions. Whether in low-light settings, varying weather conditions, or different spatial configurations, AI security systems can adapt to maintain the optimal performance. For instance, AI cameras may adjust their sensitivity based on lighting changes or modify the detection parameters depending on environmental factors like rain or fog. This adaptability ensures that security measures are consistently effective, regardless of the external conditions, ensuring that the system operates efficiently both indoors and outdoors. This makes AI-driven security systems ideal for a variety of settings, from residential homes to larger commercial and public spaces [14].
5. Conclusions
Author Contributions
Funding
Data Availability Statement
Conflicts of Interest
References
- Belaidi, H.; Meddah, N.-E.-H. Efficient Lock and Home Security System. Alger. J. Signals Syst. 2019, 4, 112–120. [Google Scholar] [CrossRef]
- Desnanjaya, I.G.M.N.; Arsana, I.N.A. Home Security Monitoring System with IoT-Based Raspberry Pi. Indones. J. Electr. Eng. Comput. Sci. 2021, 22, 1295–1302. [Google Scholar] [CrossRef]
- Alshdadi, A.A. Evaluation of IoT-Based Smart Home Assistance for Elderly People Using Robot. Electronics 2023, 12, 2627. [Google Scholar] [CrossRef]
- Kundang, J.K.; Tjahjono, B.; Yulhendri, Y.; Kadek, A. Design and Build a Room Security System Based on Internet of Things (IoT). Int. J. Sci. Technol. Manag. 2021, 2, 710–717. [Google Scholar] [CrossRef]
- Guo, X.-Y.; Wu, J.; Fang, J. Baby-Follower: A Child-Care Robot System Based on OpenMV and IoT. J. Phys. Conf. Ser. 2020, 1651, 012121. [Google Scholar] [CrossRef]
- Li, G.; Liu, Y.; Feng, K.; Pan, Y.; Liu, Y.; Yuan, M. Design of Home Intelligent Robot of Internet of Things. MATEC Web Conf. 2021, 336, 03001. [Google Scholar] [CrossRef]
- Pushpavalli, M.; Manikanta, L.N.; Sivagami, P.; Saikumar, P.; Abirami, P.; Reddy, M.V. Smart Home Automation Controlled by Robot Using MATLAB and Arduino. Int. J. Eng. Adv. Technol. 2019, 8, 1181–1184. [Google Scholar] [CrossRef]
- Kapre, S.S.; Salunkhe, S.S.; Thakkar, R.M.; Pawar, A.P.; Malusare, O.A. Advanced Security Guard with PIR Sensor for Commercial and Residential Use. Zenodo 2014, 2, 29–34. [Google Scholar] [CrossRef]
- Khan, I.R.; Jha, A.K.; Ahmad, N.; Rawat, H. Home Automation and Security Systems Using AI and IoT. In The Next Generation Innovation in IoT and Cloud Computing with Applications; CRC Press: Boca Raton, FL, USA, 2024; pp. 157–173. [Google Scholar]
- Kim, A.L.; Lee, E.J.; Kwon, H.Y.; Baek, H.M. Home Monitoring CCTV by Using Deep Learning. In Proceedings of the Korea Information Processing Society Conference; Korea Information Processing Society: Seoul, Republic of Korea, 2020; pp. 960–963. [Google Scholar]
- Jeong, J.I. A Study on the IoT Based Smart Door Lock System. In Information Science and Applications (ICISA); Springer: Singapore, 2016; pp. 1307–1318. [Google Scholar]
- Zhang, Y.; Jing, R.; Ji, X.; Hu, N. Application of Wireless Sensor Network Technology Based on Artificial Intelligence in Security Monitoring System. Open Comput. Sci. 2023, 13, 20220280. [Google Scholar] [CrossRef]
- Pasha, M.J.; Shankar, B.M.; Sivakumar, S.A.; Aswin, S.; Bragadeesh, A.; Deepak, S. Artificial Intelligence Based Intruder Detection Home Security System. Int. J. Intell. Syst. Appl. Eng. 2023, 12, 295–300. Available online: https://ijisae.org/index.php/IJISAE/article/view/3888 (accessed on 13 February 2025).
- Nguyen, T.; Lakshmanan, B.; Sheng, W. A Smart Security System with Face Recognition. 2018. Available online: http://arxiv.org/abs/1812.09127 (accessed on 13 February 2025).
- Uzoka, A.; Cadet, E.; Ojukwu, P.U. Applying artificial intelligence in Cybersecurity to enhance threat detection, response, and risk management. Comput. Sci. IT Res. J. 2024, 5, 2511–2538. [Google Scholar] [CrossRef]
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content. |
© 2025 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
Muhammad, R.; Sagara, M.S.A.; Teluma, Y.M.; Wicaksana, F.A. AI as Modern Technology for Home Security Systems: A Systematic Literature Review. Eng. Proc. 2025, 107, 35. https://doi.org/10.3390/engproc2025107035
Muhammad R, Sagara MSA, Teluma YM, Wicaksana FA. AI as Modern Technology for Home Security Systems: A Systematic Literature Review. Engineering Proceedings. 2025; 107(1):35. https://doi.org/10.3390/engproc2025107035
Chicago/Turabian StyleMuhammad, Rizki, Muhammad Syailendra Aditya Sagara, Yaunarius Molang Teluma, and Fikri Arif Wicaksana. 2025. "AI as Modern Technology for Home Security Systems: A Systematic Literature Review" Engineering Proceedings 107, no. 1: 35. https://doi.org/10.3390/engproc2025107035
APA StyleMuhammad, R., Sagara, M. S. A., Teluma, Y. M., & Wicaksana, F. A. (2025). AI as Modern Technology for Home Security Systems: A Systematic Literature Review. Engineering Proceedings, 107(1), 35. https://doi.org/10.3390/engproc2025107035