Many businesses rely on smart things for detailed status updates throughout their operations. The problem is that there are often hurdles in making platforms and devices talk to each other leading to a lot of disjointed, unconnected and unstructured data. At hellothing we demystify the elements within IoE and assist businesses in implementing solutions. We are not consulting engineers and we are not a platform. Our business model is to become technology partners to businesses in meaningful markets. Our partnership approach follows a distinct methodology:

1. Define
The first step is to define the problem that needs to be solved. We remove all the complexities that technically minded people may introduce. Once the problem is simplified the requirements are communicated to designers, engineers and project managers.
2. Create
Identify the ‘physical things’ that will interact with sensors, actuators and controllers. Identify the most appropriate communications networks e.g. GSM, BLE etc. Identify the data points e.g. temperature, humidity etc. Identify third party web services that may be used e.g. weather service. Create a user interface mock up to allow stakeholders to visualise and understand the solution.
3. Integrate
Build a prototype with continuous deployment and constant feedback. Integrate systems, middleware and third party web services. hellothing selects the best of breed platforms that are the most appropriate to the problem being solved.
4. Analyse & Automate
A rules engine is established taking into account the outputs of the sensors. Business intelligence, analytics, and customised dashboards built. Artificial Intelligence algorithms applied for machine learning and training applicable scenarios.
5. Visualise
Develop user facing front end apps or web services that can be used to manage and automate ‘Things’ through real time messaging and notifications.
6. Learn & Optimize
Continuous learning and improvement forms part of the process and what we do. With a constant inflow of data from various sources and the insights gained from humans and other systems, using and interpreting the data, AI algorithms can be trained to look deeper and understand better.
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