The Doppler Quarterly Spring 2016 | Page 27

Case Studies
The Internet of Things spans many industries , changing the way consumers collect and enhance data decision-making . The Healthcare and Agriculture markets are leading the way in IoT deployments , driven by their need to ensure safety and cost management .
Use Case Project Scope Increased Value
Cell Phone
Device
Manufacturer
Empower product quality staff to access product test results for rapid identification of supply chain problems
Migration of legacy platforms should begin with an assessment to identify :
• Critical Functionality requirements
• Gaps in existing platforms
Decrease ad-hoc queries on quality data from 12 hours to less than 30 minutes .
Healthcare Wearble Device Manufacturer
Collection of individual health data , empowering patients to self-manage lifestyle choices
To ensure proper data integrity , data must be signed at each step of the analysis process , creating a full chain-ofcustody and auditability
New capability to immediately capture vital signs and share with a medical professional .
Agriculture Technology Provider
Provide farmers with complete , accurate and up to date information for improving yields of crops
Beginning with an inventory of all existing data and systems of record ensures that duplicate data is tracked and RESTful APIs are used to limit duplication
Decrease the time needed for sharing information about a field by 50 %.
Privacy and Security Considerations
Privacy and security have an increased importance in IoT environments because of the close interconnection between consumers , devices and output from analytical engines . Privacy is key and must be implemented by guaranteeing consumers have a full understanding of and control over the data they generate and how it ’ s used .
Security must be maintained at all times to ensure that only authorized parties access and manipulate information generated by IoT devices . Security is a multilayered necessity that can be met by the Google platform through default settings , including the encryption of data in transit and at rest .
Building an IoT platform requires the ability to quickly analyze data in order to provide users with valuable , meaningful feedback and input . Google Cloud Platform provides the flexibility to deploy both Analytics @ The Edge and Analytics @ The Core models for ensuring scalable analysis in a secure fashion . Both models allow for scalability , while ensuring data stays in the appropriate location and minimizing time and risk of data movement .
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