## 2 Related Work  
DT and FL are used for several purposes. In the literature, there are a plethora of surveys discussing the application of DT and FL for healthcare, smart cities, next-generation networks, etc. In [19], the authors presented a comprehensive survey of DT's definition, use cases, applications, and challenges. This survey lacked information about FL. Another study [20] surveyed the applications, advantages, and challenges of using DT in networks. However, FL was not included in the scope of the survey. [PERSON] et al. reviewed the use of DT for the innovative purpose of businesses, the advancement of businesses using DT, and the challenges of using DT in businesses. However, the survey lacked a discussion about DT and FL for Industry 4.0 [21]. [PERSON] et al. reviewed the DT application in IoT. The survey presented detailed information on DT use cases, issues, and challenges in IoT. However, the survey lacked analysis of the use of DT and FL in IoV and IoD [22]. [PERSON] et al. explained the use of DT in the ecosystem. The survey analyzed the deployment of DT in sports. The survey only focused on the DT deployment in the ecosystem [23]. [PERSON] et al. reviewed the DT in autonomous industrial systems (AISs). The authors explained the effectiveness of using DT for the verification and validation of AISs. The survey encompassed IIoT but did not discuss FL. Moreover, the article did not explicitly discuss IoV and IoD [24]. [PERSON] et al. surveyed the implementation of DT in IoT. They presented a comprehensive analysis of the techniques for the deployment of DT and the challenges faced during the implementation of DT in IoT. The survey did not address DT and FL for IoV and IoD [25]. Similarly, the surveys [26; 27; 28] presented the use of DT in the automotive industry, prognostics, and healthcare management (PMH), and Industry 4.0 as cyber-physical systems (CPSs), respectively. However, these surveys lacked a discussion of FL for IoV and IoD. [PERSON] et al. reviewed the industrial DT at the nexus of the NGN and computational intelligence. The authors analyzed the use of DT in CPSs and NGNs. The authors also discussed the age of information (AoI). However, there is no information about IoV and IoD in this review [29]. Figure 9: Organization of the survey. [PERSON] et al. surveyed the implementation of FL for blockchain-enabled IoV. They analyzed the importance of FL and the challenges faced during its deployment. However, the survey did not include DT [30]. [PERSON] et al. explained the use of DT for IoD. The authors focused on the techniques and challenges of using DT in IoD. However, this survey did not address the use of DT and FL for IIoT and IoV [31]. [PERSON] et al. discussed the definition, technologies, security, privacy, and challenges of FL. The survey lacked information about IIoT, IoV, and IoD [32]. Similarly, the authors of [33] focused on FL for enabling technologies. The authors of [34, 35, 36, 37] focused on data privacy and security using FL. [PERSON] et al. discussed FL in IoT [38]. [PERSON] et al. demonstrated the applications and challenges of FL in mobile edge networks [39]. [PERSON] et al. surveyed the evolution of FL from distributed machine learning (ML) [40]. [PERSON] et al. focused on FL for resource-constrained IoT devices [41]. [PERSON] et al. surveyed the techniques and challenges in integrating FL and IIoT [42]. [PERSON] et al. reviewed the implementation of DT for 3D printing. Moreover, they also presented the limitations [43]. Similarly, [PERSON] et al. examined the development of DT. They provided insights into the origin and future of DT [44]. [PERSON] et al. demonstrated the implementation of IoT twins in Industry 4.0 [45]. All these surveys lacked discussion about DT, IoV, and IoD. Table 2 presents a comprehensive summary of the related surveys.