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Company: Locstat
Industry: Technology
Functional Use Case: Fraud Detection, Internet of Things/ Sensor Data, Time Series, Analytics, AI/ML

The Challenge

Headquartered in Cape Town, South Africa, Locstat connects and orchestrates multiple IoT sources of information to deliver graph-powered next-generation advanced complex event processing and a common operating picture for any defined geographical location.

The company fills a niche market in the IoT industry by providing deep analysis and predictive analytics on the sensor data IoT devices provide to companies. Built on open-source products, Locstat needed a solution that could push analytical time from two to three weeks down to minutes to generate the graphs used in their analytics. They also needed a database that could support big data and scalability.

The Solution

Locstat chose DataStax Enterprise (DSE) built on Apache Cassandra as its database and data layer, DSE Graph to power its graph imaging, and DSE Analytics to power its solution set.

Locstat uses both geospatial and real-time rules engine engineering in its products and solutions for customers across government, defense, safety and security, mining, finance, and retail industries. They built a rules engine that can not only query inline transactions, but also image all of the sensor data streaming into the environment, and then provide dashboard functionality where the end-user can see in real-time what’s going on in the environment. In addition, they store and write sensor data very quickly. “The only real database that can manage that is Cassandra,” said Ryno Goosen, Chief Technology Officer, and Managing Director, Locstat. “Machine learning is an important element of it because you want to look at predictive maintenance, especially on your sensor side. If your sensors go down, you’ll also want to look at patterns and trends in your data.”

“With Cassandra, you can move into the cloud, or private cloud, and the pain of migrating to public clouds is totally removed because you’ve got a pre-configured solution that you can use,” said Goosen. “We build on top of those elements, and if we had to manage them it would become a very costly exercise. By having our solution in the cloud, it’s the edge that we have above tier one cloud service providers because it is very difficult for them to compete. That is a huge advantage for us playing in these markets.”

For illustration, Goosen shared a Geotrellis generated heat map with flight data from aircraft and flight patterns around the Cape Town International Airport. In this example, data is stored in Cassandra and then pushed through Apache Spark and visualized using Geotrellis in a Cesium spatial interface. According to Goosen, this visualization enables the ability to “layer flight patterns in real time automatically in the application and select alternative spatial maps when you want additional context layers in the background of the application.”

“We built a rules engine that can not only query inline transactions, but image all of the sensor data streaming into the environment, and then provide dashboard functionality where the end user can see in real time what’s going on in the environment. In addition, we store and write sensor data very quickly. The only real database that can manage that is DataStax.”

The Results

Powered by Cassandra and other open source solutions, Locstat is able to provide its clients with innovative IoT solutions, such as geospatial risk management for a marine mining company that uses ships to extract minerals from the sea bed. This customer is able to set up Locstat to provide a risk early-warning zone around the ship that moves with the vessel. The system provides information on other vessels and craft entering the ship’s vicinity and triggers alerts if those vessels reach a certain threshold. Daily reports let them track which vessels pose risk to their ships. Locstat also provides this risk management solution for aircraft and drone surveillance vendors.

The company also helps combat copper cable theft by analyzing incident reports, remote sensors, proximity to impoverished areas, transportation hubs, and scrap metal dealer locations to predict higher likelihood for copper theft. They have helped specialist security company Amahlo Consulting reduce copper theft for one of their clients over a three-year period by up to 68%.

They also work in fraud prevention helping to analyze more than 25 million data transactions and four million financial transactions per day for a financial services customer. DSE powers their ability to manage high volume data and analytics, with the ability to scale and the reliability of zero downtime.

Stack Includes: AI/ML, Apache Cassandra, Apache Spark, Datastax Enterprise

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