Case study: Integrating IoT, streaming analytics and machine learning to improve intelligent diabetes management system
2017 International Conference on Energy, Communication, Data Analytics and Soft Computing (ICECDS)
Today petabytes of data are stored in healthcare sector such as clinical and pharmaceutical and a... more Today petabytes of data are stored in healthcare sector such as clinical and pharmaceutical and academic research archives. Trillions of structured and unstructured data are continuously streaming from wearable sensors such as activity trackers, continuous glucose monitoring devices, and implantable defibrillators. Present day machine learning diabetes management applications are helping numerous patients to live healthier lives by having easy access to advice and information from health specialists. The advent of digital devices and sophisticated analytics has attracted traditional companies into the digital revolution. The paper studies how Zion China technical solution E-Followup which was based mostly on traditional Business Intelligence with data sourced from on-premises and various devices or cloud storage. In this engagement, they wanted a smart, fast, and cost-effective way to continuously feed data from devices to the cloud and had other technical goals. The result provide an insight how they handled massive data volumes efficiently and improved analysis of data.
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