Problem Statement

It has been observed that oil theft is happening across the world. As per estimation around $ 133 billion worth oil is stolen every year. The major portion of oil pilferage is considered to be caused by supply tankers. Supply management is considered to be the backbone of industries and suppliers play vital roles in that. So in our case study will be focusing on oil supply tankers.

In our case study we will be focusing on IoT services and will be skipping the IoT device part with the belief that we are getting a JSON payload from our devices on our MQTT endpoints.

We will be getting the following JSON payload into our AWS Cloud with the following information: Tanker Id(TID) , Tanker Capacity(CAP), Quantity Delivered(D_QTY), Point of Delivery(LOC) and Available Capacity(A_CAP).

AWS provides us with many IoT services. The services we will be using are AWS IoT Core , AWS IoT Events and AWS IoT Analytics for this case study.

As per the above architecture,the devices are sending their payloads to AWS IoT core using MQTT protocols. AWS IoT Core sends those payloads to AWS IoT Events and AWS IoT Analytics completes analysis by defining rules and executing actions. AWS IoT Events allow us to set up an event based alert system which notifies concerned authorities using Amazon SNS (Simple Notification Service). Whereas for reports and graphical insights AWS Analytics is used. The desired analytics as per business requirements are performed on the real time dataset created by payloads.

IoT Event service monitors the data and creates a notification when an abnormality is observed by triggering an event. In our case it issues the notification by sending an email when a tanker supplies oil at an unknown location, quantity supplied is not as per supply plan or if the quantity supplied exceeds available capacity as per the oil terminal.

Insights

AWS IoT analytics allows to perform analytics on the data received from IoT devices to monitor, track pilferage and other information to improve oil supply.

Above graph allows us to track oil tanker supply in terms of how much quantity supplied at which delivery point along with the available capacity as per oil terminal record. The red dotted box shows that at station ST8 and ST9 fuel supplied exceeded the amount of available oil. This implies that more fuel is added into the tanker from some other source which degrades the quality and leads to customer disappointment and business loss.

This graph shows the amount of fuel delivered to various delivery points from each tanker. Here the red dotted box indicates a station name UNK which is not mentioned in the supply plan. UNK is the point where fuel pilferage occurred by tanker with tanker id ACK352.
Secondly A,B & C shows the minimum , average and maximum amount of fuel supplied by the fleet.

Benefits

• Real time delivery of data.
• Pilferage triggers a notification to a responsible stakeholder through email.
• The point of pilferage can be identified.
• Track of Supplies and culprit will be identified.
• Product Quality will not be compromised by avoiding addition of substandard fuel into the tanker by tanker driver.

Pricing

AWS IoT services will roughly cost around $5.00 for implementing the above architecture along with the end to end execution for 5 supply plans. This may vary as it depends on the size and frequency of the data you are passing.

For an AWS User who is new to AWS IoT services can avail free tier.