## 7 Feasibility, Scalability, and Performance Evaluation
### The mPOC Performance Evaluation  
In this section, the performance evaluation of the mPOC prediction model is analyzed. The mechanism involves capturing physiological data from users, which can be susceptible to unwanted noise and occasional faulty readings. To enhance the specificity and sensitivity of the diagnosis, appropriate filtering techniques, such as Kalman filtering, are employed [47]. The second mode of operation relies on the timely delivery of real-time health and outbreak information by the authority, necessitating the establishment and maintenance of anytime and anywhere connectivity. This is generally not a challenge in metropolitan areas. The third mode of operation involves establishing proper device-to-device (D2D)connections with community members for information exchange. Since no multimedia data, such as voice, video, or images, are transmitted across the network, there is no need to maintain a high-quality communication link. The transmitted information is in the form of text, allowing for some degree of delay. The mPOC system is capable of tracking the physiological signs of users during the advanced stage (AS) if they require the attention of a healthcare professional while self-isolating at home. For the end-to-end performance evaluation, we utilized LabVIEW Community Edition [45], simulating the mobile/Bio-Watch user, the Outbreak Tracking Center (OTC), and various infection clusters. The algorithm (Figure 3) is deployed and simulated revolving around the movement of the mobile user from a low-risk area (residence) to various high-risk areas. The local visual and auditory feedback systems were utilized and recorded during the movements. Figure 4 illustrates the achieved accuracy based on the movements from a Low-Risk Location (LRL) to a High-Risk Location (HRL) and vice versa. The performance scatterplot demonstrates that the accuracy measures for correctly identifying the user's risk when moving from one LRL to another LRL are at the highest levels, with a mean value of 92.8% accuracy with the variations ranging from 91% to 95%. The accuracy measures slightly decrease for movements from LRL to HRL, with a mean value of 87.08% accuracy with the variations between 85% and 90%. The accuracy measures further decline for movements from HRL to HRL, with a mean value of 84.84% with the variations between 83% and 88%. This decline can be attributed to the increased utilization of the algorithm to capture, transmit, and interpret the rapidly changing parameters. The accuracy measures display high variation during movements from HRL to LRL, with a mean value of 84.12% and significant variations between 79% and 89%. This variation is influenced by differences in parameter reporting between high- and low-profile locations. A crucial aspect of the application that needs to be addressed is the security and privacy capabilities of the mPOC system. Since mPOC users are within the D2D wireless range of each other (within 500 m), they will receive personalized DRI and PEI values from other users, which are to be passed to the OTC. To address security and privacy requirements, each mPOC system is assigned a unique anonymous 10-digit code, which remains private and secured from all users. All communication channels between mPOC users are encrypted to prevent Man-In-The-Middle Attacks, ensuring that adversaries cannot impersonate valid users or hijack established communication channels. The OTC stores and maintains the list of validated secure codes for all users in its database. Although the accuracy versus movement performance measure is by far the most important performance measure that can be considered in this article, other metrics can also be used to study the performance of the mPOC system, such as:  
1. The economical, operational, social, legal, ethnical, scalability, and sustainability aspects of the mPOC system;
2. The feasibility and readiness of the elderly and non-tech savvy users to use the mPOC technology for disaster management;
3. Delay studies for OTC to reach end-users;
4.