Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: A promising architecture for remote healthcare monitoring involves the use of a pervasive device (such as a cellular phone), which aggregates data from multiple body-worn medical sensors and transmits the data to the backend. Unfortunately, the volume of data generated by increasingly sophisticated continuously- active sensors can overwhelm the resources on the mobile device.  propose imbuing the mobile device with the intelligence to perform context-aware filtering of sensor data streams in order to reduce transmissions in cases where the observed data corresponds to the norm expected by the system in a given context. To investigate the efficacy of this technique,  implemented the HARMONI middleware on a mobile device, and used it to collect real sensor data from users. Our experiments demonstrate that context-aware filtering can reduce the uplink bandwidth requirements of the system by up to 72%.
['I. homed', 'Archan Misra', 'Maria R. Ebling', 'William F. Jerome']
I am writing a research paper on a idea HARMONI: Context-aware Filtering of Sensor Data for Continuous Remote Health Monitoring
[{"from": "human", "value": "I am writing a research paper on a idea HARMONI: Context-aware Filtering of Sensor Data for Continuous Remote Health Monitoring"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: A promising architecture for remote healthcare monitoring involves the use of a pervasive device (such as a cellular phone), which aggregates data from multiple body-worn medical sensors and transmits the data to the backend. Unfortunately, the volume of data generated by increasingly sophisticated continuously- active sensors can overwhelm the resources on the mobile device.  propose imbuing the mobile device with the intelligence to perform context-aware filtering of sensor data streams in order to reduce transmissions in cases where the observed data corresponds to the norm expected by the system in a given context. To investigate the efficacy of this technique,  implemented the HARMONI middleware on a mobile device, and used it to collect real sensor data from users. Our experiments demonstrate that context-aware filtering can reduce the uplink bandwidth requirements of the system by up to 72%."}]