# An Overview of Machine Learning and 5G for People with Disabilities
## 6 A 5G Network Slicing Architecture for People with Disabilities
### People with Disabilities Slices Design  
Network slicing in 5G networks enables that, in the ecosystem of people with disabilities, different tenants (customers) issue requests to an infrastructure provider for acquiring network slices to cope with a wide range of use cases. The most relevant Key Performance Indicators (KPIs) of the different use cases, for people with disabilities, are summarized in Table 1.  
The end-to-end latency has been measured as the time it takes to transfer a given piece of information from a source to a destination, measured at the application level, from the moment it is transmitted by the source to the moment it is received at the destination. Additionally, 3 GPP has classified 5G use cases into three categories: eMBB, mMTC, and URLLC (see Section 3.6). Although it is not clear cut to which category a use case belongs to [68], based on the main KPIs and functional requirements of the different use cases for disabled, we propose the following slices:  
* _Navigations systems for the visually impaired_: URLLC requirements. * _Object recognition systems for the visually impaired_: URLLC requirements. * _Facial recognition systems for the visually impaired_: URLLC requirements. * _Sound recognition systems for the hearing impaired_: URLLC requirements. * _Videoconterence with ASL recognition_: eMBB requirements. \begin{table}
\begin{tabular}{c c c c} \hline \hline \multirow{2}{*}{**Use Case**} & **End-to-End** & **Data Rate** & \multirow{2}{*}{**Reliability**} \\  & **Latency** & **(Uplink/Downlink)** & & \\ \hline Navigations systems for visually impaired & 10 ms & 25 Mbit/s/1 Mbit/s & 99.999\% \\ \hline Object recognition systems for visually impaired & \textless{}20 ms & 25 Mbit/s/1 Mbit/s & 99.999\% \\ \hline Facial recognition systems for visually impaired & 10 ms & 25 Mbit/s/1 Mbit/s & 99.999\% \\ \hline Sound recognition systems for hearing impaired & \textless{}20 ms & 1.5 Mbit/s/10 Mbit/s & 99.999\% \\ \hline Videoconference with ASL recognition & 4 ms & 500 Mbit/s/1 Gbit/s & 95\% \\ \hline \multirow{5}{*}{
\begin{tabular}{c} Smart homes (UE to network) \\ \end{tabular} } & Home appliances, electronic UE (e.g., \\  & printers) or IoT devices (e.g., smart \\  & flower to water a plant) & 10 ms & 500 Mbit/s/1 Gbit/s & 95\% \\ \cline{2-4}  & Wearables (sensors embedded in \\  & clothing, UE monitoring biometrics) & 10 ms & 10 Mbit/s/10 Mbit/s & 95\% \\ \cline{2-4}  & Real-time video/telepresence for \\  & remote healthcare & 100 ms & 40 Mbit/s/40 Mbit/s & 99.999\% \\ \hline Remote driving (information exchange between a UE \\  & supporting V2X application and a V2X application server) & 5 ms & 25 Mbit/s/1 Mbit/s & 99.999\% \\ \hline \hline \end{tabular}
\end{table} 
Table 1: KPIs of the different use cases for people with disabilities [50; 65; 66; 67]. * _Smart homes for handicapped (see Section 4.4)_: We distinguish between different areas that require automation and control in smart homes [55]:
* _Health monitoring_: falls and balance, first aid and emergence service, vital signs monitoring, telemedicine, etc. * _Behavior monitoring (to learn the user's habits and alert caregivers and family members of any significant changes)_: medication habits, diet, sleeping patterns, etc. * _Security_: intruder detection, fire alarm, automatic door lock, kitchen equipment control, etc. * _Environment (home automation and smart appliances)_: AC control, heating control, water temperature control, light control, etc. * _Entertainment_: TV on/off, channel/movie selection, daily exercise, etc. The proposed smart home 5G network consists of _three slices_:
* _A healthcare and behavior monitoring network slice [69]_: it is reserved for the use of healthcare professionals and caregivers to help the disabled person (remote healthcare); it has eMBB requirements. * _A security slice_: to ensure isolation, this slice has its own VNFs for the access and core network; it also has its own AUSF for the authentication of devices before they gain access to the slice; it has URLLC requirements.