# Approaches and Challenges in Internet of Robotic Things
## 3 Related Work  
### IoRT: An Outline  
IoRT is a fusion of several disciplines such as robotics, cloud computing, AI, and the IoT [2]. IoRT allows robotic objects to participate actively in diverse environments. In diverse surroundings, the robotic objects share data with other robotic devices, IoT devices, and people [3]. IoRT's most recent concepts, technologies, and challenges are useful for the future progress of robotic systems. The application of the IoRT system can be further intensified in industrial production and development, agriculture, and other areas of human importance [6]. [PERSON] et al. [3] showed a three-layer architecture of IoRT including related technologies such as actuators and sensors, and the Bricks View-RoIS. In addition, the authors of [3] presented HRI challenges and related charts for service robots. In [1], an IoRT architecture was recognized and understood considering five layers: robotic, network, Internet, infrastructure, and application layers. The infrastructure layer includes the robotic and M2M2A cloud platforms, IoT commercial cloud facilities, and IoT  
\begin{table}
\begin{tabular}{p{113.8 pt} p{113.8 pt} p{113.8 pt}} \hline \hline
**Author** & **IoRT Domain** & **Architecture** \\ \hline
**[PERSON] et al. [1]** & IoRT—infrastructure & Five-layered \\ \hline
**[PERSON] et al. [3]** & IoRT—applications & Three-layered \\ \hline
**[PERSON] et al. [6]** & Intelligent robotics & Five-layered \\ \hline
**[PERSON] et al. [46]** & IoRT—architecture and components & Three-layered \\ \hline
**[PERSON] et al. [47]** & IoT—energy efficiency and interoperability & Three-, four-, five-, and seven-layered \\ \hline
**[PERSON] et al. [48]** & IoRT—security and privacy & Three-layered \\ \hline \hline \end{tabular}
\end{table}
Table 5: A survey of layered IoRT architectures.  
cloud robotics setup. The main capabilities of the five-layered architecture are awareness, interoperability, extensibility, virtualized diversity, dynamic, and self-adaptive behavior. The authors of [22] described the enabling technologies of the robotic system such as robots, AI, ANN, ML, fuzzy logic, and swarm technology, along with their application. The future difficulty of IoRT is data connectivity and security, which require a great deal of attention [7]. Gaze tracking, speech recognition, and biological recognition are HRI issues encountered by IoRT. HRI problems have not yet been put to the test. Instead, HRI issues are mostly being investigated. Computational issues, optimization, security concerns, and ethical concerns are among the IoRT challenges [3; 5; 11]. In our study, a taxonomy of IoRT, including IoRT technologies and capabilities, is proposed in Figure 9. IoRT, as we know, is a mix of different technologies, such as AI, which aids in intelligent decision making, and cloud robotics, which aids robots by employing cloud infrastructures such as cloud computing, cloud storage, and connectivity technologies. The Internet of things focuses on sensing, monitoring, and tracking, whereas robotics focuses on interactions, navigation, etc. [4]. As seen in the taxonomy graphic, all of these technologies interact with one another.