A coordinator‐specific privacy‐preserving model for E‐health monitoring using artificial bee colony approach. Issue 4 (15th August 2018) - Dhasarathan, Chandramohan; Dayalan, Rajaguru; Thirumal, Vengattaram; Ponnurangam, Dhavachelvan
Abstract : In the contemporary scientific world, unpredictable health‐related issues and tribulations are changing into new diseases for the next generation. Medication and its treatment levels have advanced to the next level to support the human race. A patient's regular health check‐up in hospices and continuous guidance from a practitioner are added as habitual in a typical human life. However, it might not support patients who escalate to critical care in a fraction of minutes. As a sustaining connotation for healthcare, body sensors (BS) have been espoused for the regular monitoring the patients; irrespective of the patient's daily activities, BS follows him or her like a shadow without his or her intervention. The sensed information is transmitted to the medication department exclusively, and it is expected to reach the concerned practitioner, most importantly without delay and intervention. The health information which are generated at critical situations, have to be traversed to reach the healthcare system. There is a need for network miniaturization to process the patient health information. There are issues pertaining to data forecasting of the base station or healthcare management system. This paper particularly focuses on the coordinator‐specific optimized healthcare monitoring through patient data forwarding during normal, emergency, and critical cases. However, if every patient has his or her own device, that is, bring your own devices (BYODs), then there arises a data privacy problem for sharing resources in BYODs. For organizing the smart device resources, there might be an optimization technique to allocate resources in the network frame due to its mobility and ad hoc nature. To perform the resource allocation process, the proposed system adopts the artificial bee colony approach for the evolution of information collected from the patient's sensors for a precautionary medication process. The efficiency of the proposed system is evaluated using existing techniques. The experimental result analysis shows that the proposed system performance is high in all scenarios, and moreover, it maintains a high reliability rate in delivering sensitive data more effectively.