With increasing network complexity, intelligent mechanisms to efficiently achieve the required quality of service of wireless-enabled applications are being developed, especially for industrial environments due to the onset of the fourth industrial revolution. In this paper, the potential benefits of wireless channel quality prediction for two of the three major use cases supported by 5G viz. enhanced Mobile BroadBand (eMBB) and Ultra-Reliable Low Latency Communication (URLLC) are quantified in an industrial indoor environment through simulations. Our analysis shows that the ability to perform perfect prediction improves the 10th user throughput percentile by up to 125% for eMBB use case and decreases the 90th resource utilization percentile by up to 37% for URLLC use case. Furthermore, the maximum tolerable prediction inaccuracy is found to be up to 5 dB and 0.35 dB for eMBB and URLLC use cases, respectively.

Shorter hospitalisation is a strategy that healthcare services have adopted to solve the problem of high demand for hospitalisation under conditions of insufficient resources. Early discharge demands patients to self-manage their recovery at home, while recovery is still perceived a clinician’s responsibility. This often results in an extra emotional and psychological load on patients. Due to the lack of measurements to include the emotional and psychological state of a patient in the home context, clinicians often oversee these issues in the evaluation of patients' recovery during hospital visits. This paper outlines the development of esther 1.0, an electronic tool based on Experience Sampling Method, that encourages senior patients of Total Hip Replacement (THR) to self-report their experiences related to their perceived physical and emotional state during the first weeks of recovery at home. This paper describes the emotional assessment of a THR patient and reflects on the value of this knowledge to develop professional support beyond the clinical recovery.