- Application Infrastructure & Middleware - Database Management & Storage
- Cybersecurity & Privacy - Identity & Authentication Management
- Functional Applications - Remote Monitoring & Control Systems
- Sensors - Biometric Sensor
- Sensors - GPS
- Healthcare & Hospitals
- Business Operation
- Remote Patient Monitoring
The client faced challenges in their attempt to improve patient care through objective data gathered from smart products such as Apple Watch, Fitbit, Carbon, and Samsung Gear which relates to patient compliance with prescribed medication regimen and their lifestyle patterns. The client was searching for an appropriate analytics algorithm which would help them gain actionable insights from the unstructured data. The backend came with a hive table which helped import data to the Hadoop environment. The company faced roadblocks in extracting behavioural context over time to tailor treatment according to the needs of patients with Serious Mental Illnesses (SMI). They aimed at developing a passive sensing mobile application which would enable full control and surveillance of the patients.
To ensure that the patients remain compliant with the prescribed drug regimen, the client gathered data from mobile sensors such as barometers, pedometers, and GPS (providing insight into the distance traveled by the patient).
The client also endeavored to gather data from call logs to ascertain how many calls were made and how the client interacts with the external world. The parameter-defined data is collected at regular intervals and sent to the backend, following which Cartesian coordinates and maps are used for calculation.
HCL’s dedicated Internet of Things (IoT) business unit, IoT WoRKSTM , facilitated the development of a Passive Sensing Mobile Application for both Android and iOS platforms, by deploying HCL’s in-house Medical Mobile Application (MMA) platform. This platform, also an SDK, would ensure faster and standardized development of the Passive Sensing Mobile Application. In the first phase, the application was developed for patients as users, but was extended to other stakeholders such as healthcare providers.
As a part of the project, IoT WoRKSTM would enable a backend system both for data storage and authentication.
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