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Sensing Technologies for Societal Well-Being: A Needs Analysis
Abstract
Sensing technologies by design are calibrated for accuracy against an expected measurement scale. Sensor calibration and signal processing criteria are one type of sensor data, while the sensor readings are another. Ensuring data accuracy and precision from sensors is an essential, ongoing challenge, but these issues haven’t stopped the potential for pervasive application use. Technological advances afford an opportunity for sensor data integration as a vehicle for societal well-being and the focus of ongoing research. A lean and flexible architecture is needed to acquire sensor data for societal well-being. As such, this research places emphasis on the acquisition of environmental sensor data through lean application programming protocols (APIs) through services such as SMS, where scant literature is presented. The contribution of this research is to advance the research that integrates sensor data with pervasive applications.
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