# A Review: Image Processing Techniques' Roles towards Energy-Efficient and Secure IoT
## 4 Literature Review
### IoT Safety Applications Based on Image Processing  
Image processing in the field of smart cities and IoTS has given rise to a variety of demands and purposes. Image processing has been put to use in an innovative application that aims to improve road safety for motorists and pedestrians by detecting and identifying road targets. Once object recognition has been performed, a reinforcement learning (RL) algorithm based on artificial intelligence (AI) is used to send information to a robot or wearable device so that the user can understand and interact with it to make a decision [53].  
The use of face recognition in an OCR-based smart support system is one such example [54]. The proposed system relies on captured images for object detection and recognition so that the visually-challenged person would be supported and led without the requirement for an actual supporter.  
Precious and digital assets, such as in workplaces, are deemed to contain sensitive data. A higher level of confidentiality for the relevant information should have been attained via their protection. To provide secure access to such workplaces, there should be a verification of the identity (ID) of the person who is attempting to access them. A face-based matching mechanism will be necessary. Using an image analysis method and a matching process, the proposed IoTS analyzes an image of a person's face and stores the results. Authorized access may be granted if the face is accurately identified. By doing this, digital assets may be kept private [55].  
The IoT has garnered increasingly more attention in recent years. On the other hand, IoT terminal devices take images that are intimately connected to the users' personal information. This information is private and must be protected from unauthorized access. For example, homomorphic encryption primitives may make it easier to keep outsourced computing private, but they use a significant amount of CPU and storage resources in the process. Because of this, IoT terminals with limited resources are put to the test. An architecture for outsourced image processing that includes edge-assisted privacy preservation, image retrieval and classification has been proposed here in order to minimize the amount of resource consumption by terminal devices. To safeguard data while using cloud computing, a semi-trusted cloud server relies on nearby edge nodes. Edge-assisted privacy preservation is presented for image retrieval and classification [56]. An illustration related to IoT safety applications based on image processing is shown in Figure 5.  
IoT terminal devices' computation, communication, and storage loads may be greatly lowered by the recommended ways. Another method of content security based on image processing is presented [57]. Once the image has been captured, a cryptographic strategy is employed. Then, it was transmitted to another server. In addition, a cover image security mechanism is added to the cryptographic image. A cover image will then include the encrypted image. The last step is to upload the cover image to the cloud via the IoT platform.  
Examples of IoTSs that use image processing techniques could include machine safety and environmental monitoring [58], the agricultural industry's plant growth surveillance for improved safety in such a process [59], or the detection of a disease location on plants [60].