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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