Appian being low code is an exciting platform to work. It is always a prioritized choice to develop a digital solution POC in a tight timeframe with low overheads. Current digital trends and their day to day application in power utility domain is a very intriguing topic where it is always felt that ‘let’s add some more to the sauce..’
Appian’s seamless mobile interface and integration capability are key considerations to build such solutions which can be used by on field technicians and does not cause interference in their work task.

What it does

Smart Grid comprises of multiple IOT devices collecting data to enable the tracking and monitoring of the transformers. Depending on the condition of the data received, the application then executes smart routing to the corresponding substation control expert teams who provide specialized care and handling of the transformers and wires.

How I built it

We collaborated with the IoT team to integrate Appian with the sensor devices placed across the locations. The sensors collect real-time data on wind speed and oil levels to monitor transformer conditions. We Leveraged Appian's Goggle Cloud Vision connected system template to perform image analysis for galloping wire. we integration with AR to analyze the case to fix it. We used Goggle Maps component plug-in & Connected System template to search and show the substation locations for fixing the issues in the transformers. We worked towards figuring scenarios where Appian dynamic case management, decisions and rules, AI could be used. Google Chart framework has been used to build reports to provide actionable insights for efficient tracking of transformers.

Challenges I ran into

The challenge was to collect real-time sensor device data and images from across multiple real transformer device/location to test and realize the true functioning of the app. We faced challenges in preparing the required amount of training datasets for training ML model. Showing the live sensor data in Appian screens to reflect real-time updates of Sensor data was also challenging.

Accomplishments that I'm proud of

Integrating with the IoT sensor devices to capture real-time sensor data, making use of Google Maps component-plug-in and connected system plug-in to bring power of Google place search and map view into Appian to enable convenient location look up, integration with cloud vision to perform image analysis, creating intuitive and beautiful user interfaces using Appian SAIL.

What I learned

Ease of implementation, agility, adaptability often define the next course of action.

What's next for test

To leverage AWS, Google AI and implement the AI component leveraging more factors for efficient predictive system.

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