{"id":1203,"date":"2016-01-07T10:29:47","date_gmt":"2016-01-07T04:59:47","guid":{"rendered":"http:\/\/www.allerin.com\/blog\/?p=1203"},"modified":"2016-08-10T18:55:26","modified_gmt":"2016-08-10T13:25:26","slug":"the-3-facets-of-developing-an-iot-solution","status":"publish","type":"post","link":"https:\/\/www.allerin.com\/blog\/the-3-facets-of-developing-an-iot-solution\/","title":{"rendered":"The 3 facets of developing an IoT solution"},"content":{"rendered":"

Organizations are struggling to understand how Business Intelligence (BI) analytics and the Internet of Things (IoT) can help them or what technologies will be needed to deploy IoT solutions.<\/p>\n

The distribution of applications to edge sites in IoT makes solutions complex to deploy, manage and maintain. Couple that with the fact that many BI practitioners lack the expertise of streaming analytics, time series data management and other technologies used in IoT analytics, and you have a sizeable challenge.<\/p>\n

Let\u2019s explore some of the ways using which Allerin can help you develop an ideal IoT solution.<\/p>\n

Facet #1 – Acquiring and storing your data<\/h3>\n

Countless protocols are available that allow the receipt of events from IoT devices. It is not important whether the device connects to the network using Bluetooth, cellular, Wi-Fi, or a hardware connection. What\u2019s important is if the device can connect and send a message to a broker of some sort using a well-defined protocol. Irrespective of what protocol you end up using, once the message is received, the message then can be handed over to the analytics system.<\/p>\n

Facet #2 – Reprocessing and transformations<\/h3>\n

Data that is acquired from devices in their raw form are not necessarily suited for analytics. Data might be missing or may have to go through an enrichment step, or representations of values may need transformation. A pre-processing step will always be needed to manage enrichments and transformations. Although there are multiple ways to structure this, the best practice is to store the transformed data along with the raw source data.<\/p>\n

Facet #3 – Analytics for business insights<\/h3>\n

After the data has been transformed into a suitable state and has been stored for future use, it is analysed using analytics tools.<\/p>\n

Our value proposition<\/strong><\/h3>\n

Allerin\u2019s IoT solutions enable organisations to handle continuous streams of data in an efficient, scalable manner. The framework developed by Allerin excels at managing high-volume streams and performing operations over them, which includes events like correlation, rolling metric calculations, and aggregate statistics.<\/p>\n

The IoT trend will have a huge impact across all sectors, but cashing on the trend won\u2019t be simple unless you have a solution that caters to your particular industry and understand the problem that exists in those sectors. This is exactly where Allerin\u2019s IoT framework comes into play, and can benefit organisations across sectors by providing them with tailor-made IoT solutions.<\/p>\n","protected":false},"excerpt":{"rendered":"

Organizations are struggling to understand how Business Intelligence (BI) analytics and the Internet of Things (IoT) can help them or what technologies will be needed to deploy IoT solutions. 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