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| Author | Function | Cloud | Accuracy | Customization |
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| [14] | Raspberry Pi 3 Model B-based home security system was implemented with the Haar cascade algorithm and HOG | A cloud server is not implemented in this study | Accuracy of security system: Raspberry Pi 3: 100%; PIR sensor based: 76% | Customization is limited in this study for real-time implementation |
| [11] | Raspberry Pi with Yolo and Haar techniques are used to implement a human intrusion detection system | The cloud server is employed to store the detected intruder photos | 83% accuracy for frontal face detection. 96% face or eye detection | Only Raspberry Pi is used for real-time implementation |
| [12] | MATLAB along with Raspberry Pi is used to detect emotions through speech | NA | Recognition efficiency: 85% in MATLAB and 95% on Raspberry Pi 3 | The study implemented ready-made boards for the real-time implementation |
| [13] | The Haar cascade (face detection) and LBP (face recognition) algorithms are preferred for the real-time implementation of a system for monitoring the security with Raspberry Pi 2 | The cloud server is used to store variations in motion | Accuracy is not discussed in this study | Raspberry Pi 2 is used for the implementation of the system |
| [15] | Integration of Viola–Jones algorithm, oriented FAST and rotated BRIEF (ORB) and SVM-based system is proposed for detecting suspects | The proposed classifier is stored and trained in the cloud | The algorithm’s performance will improve with a better classifier | To investigate the performance of face detection algorithms on real-time video streams on the Raspberry Pi device |
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