Omnitribe is a Proptech company whose cloud-based products vertically integrate tenant experiences and building operations with a mission of providing autonomy, automation and insights. Omnitribe has built a platform providing innovative technology solutions for security practitioners and building owners to manage visitors, tenants, vehicles and vendors.
We are in the process of building a new smart car park application, which would give parking lot administrators insights into how their facilities are being used, and how they can take action in real-time based on their operating requirements.
Before the final implementation, we would like to test a few use cases and workflows to ensure that the application works according to our requirements. This way, when deploying with devices on site, this will help smooth the integration and there will be a lot less troubleshooting.
At a high level, we aim to test our workflows and ideas in real physical spaces, where for this project electromagnetic sensors would need to be deployed in a location that has traffic with parking lots (e.g. a car park).
However, this is challenging because it is:
a) hard to find a suitable location
b) it is time consuming and costly to create a test environment on a small scale.
Usually, we will need to identify a site that allows us to test our ideas on a small scale. This is very difficult to find, time consuming and very inefficient with cost. Testing will also be difficult because the devices will be on site and if there is anything wrong, or if we need to trigger certain values manually, we will need resources there. Which is not ideal for us as we are a small outfit.
We realized that Gravio can provide a quick test bed by mimicking ‘real-world’ situations.
Firstly, through the use of battery-operated door/magnetic sensors that work with Gravio out of the box, we could simulate the scenario where a car enters a parking spot, represented by the magnets connecting in place i.e. the car parks and becomes stationary.
By taking this approach, we also removed at least 1 layer of integration from hardware to software, which allowed us to get started faster and more easily, without leaving the office.
Taking this approach, we were then able to simulate a small car park using paper and a number of magnetic sensors, which were used to simulate and therefore determine the vehicles and the spaces available in the parking lot.
As mentioned, we could then easily test our environment internally whilst building the application by using the magnetic sensor data as available or occupied parking lots: open for available lots and closed for occupied lots. We have integrated this into our backend, which is hosted using Amazon Web Services (AWS), using one of Gravio’s software component modules in the Actions editor which was hassle free.
As a small team we are always trying to find ways to improve our methods of testing and development. Currently, even in other projects, our team identifies a test site and does various forms of set up which is tedious and time consuming. As resources are limited and time is very precious, we have to find new ways of improving our work and make it more efficient.
We found out about Gravio because we knew Nicholas Lim, a Gravio Evangelist, from previous working relationships. As we communicate regularly with regards to IoT or even talking about solutions and ideas, he identified gaps for us and how Gravio can fill certain gaps. That was how Gravio was recommended and when we saw a demo, we were very excited about this technology!
Getting started was relatively smooth with a small learning curve. The user interface was made to be quite user friendly. The first set up was to learn how to understand edge computing and how it works, by connecting the sensors that were made available to us. We understood how data was streaming in and how we could quickly create applications from the widely available choices that are already integrated with Gravio.
We were also impressed with not only the hardware connectivity but also the software components that are available. One example is the AWS integration which we use very often and also Teams which we use daily for work communication and collaboration.
Definitely! The most immediate effect was that the sensors Gravio offered out of the box could be applied in many smart offices very quickly due to its short learning curve and easy to use interface. Progressively understanding the advanced features of it, it could also be used in complex IoT projects. With the integrated components, it accelerates software development and reduces development time greatly. At that point, we felt that the possibilities were endless!
We also have done a couple of internal tests with our own unmanned Visitor Management System, Litehaus. Its purpose is to help with contact tracing and also manage visitorship for an area, for example, shopping malls or schools. Litehaus achieves this by having crowd analytics using a combination of distance, motion, vibration, CO2 and inference models. Currently, we have used Gravio to test out playing audio files when motion is detected near Litehaus. We believe that this will also increase user experience when using an unmanned kiosk such as Litehaus.
This is definitely not the final product of our application. It is still in a very early stage but what Gravio has done is made our testing process a lot more streamlined and efficient. This is because we can now test everything we need in our office! We will definitely want to show the completed product and application once it is completed. Thank you!
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