In the future, more and more devices will be connected to the internet – analysts are projecting this number to reach 50 billion devices by 2022.

IoT will be used in cars, factories, agriculture, smart building, healthcare, homes, cities and so on. IoT devices generate sensor data such as state and other metrics, send event notifications, generate video data and need to be remotely controlled. With the sheer volume of sensor data there is clearly a challenge to transfer and conduct smart analytics and machine learning in real-time, while combining historical state and other external sources.


Managing Different Types of Data

Managing all data types from various sensors in one place

Volume and Velocity

Processing huge amounts of data in real-time

Event-Driven Applications

Real-time alerts on abnormalities

Fine-Grained Security

Strict authentication and access control

Case Study – Connected Car

A multinational automotive corporation built an IoT connected truck solution for predictive maintenance and proactive analytics. The corporation used iguazio’s Continuous Data Platform to collect, analyze and act upon smart mobility data in real-time, generating insights for all parties involved in the value chain, from engine manufacturers to logistics companies.


The Challenge

The automotive corporation manufactures and manages millions of vehicles worldwide and therefore aggregates huge amounts of data. As part of its strategy to provide innovative financing, leasing, fleet management, insurance and mobility services, the corporation needed a solution that ingests, processes and analyzes data coming from numerous sources in real-time. Since sensors placed in trucks constantly upload data, storage costs can be extremely expensive. In addition, new paradigms of strict access control had to be implemented as IoT brings up major security concerns. The corporation was seeking a new solution that could address its enterprise requirements while eliminating complexities.

The Solution

The iguazio Continuous Data platform provided a turnkey solution incorporating machine learning tools that were applied on the data in real-time. iguazio’s platform handles all forms of data in an IoT application – ingesting sensor data which included state, statistics and event streams while triggering alerts when immediate attention was required by using serverless functions (e.g. device failure and temperature beyond normal). Data was enriched with external data such as weather conditions and correlated with historical state, all in a matter of seconds. This enabled the corporation to explore latest insights at any given time and make machine learning-based predictions to anticipate possible malfunctions and events. Furthermore, the platform enabled device configuration in a flexible schema and maintained durable message queues per device for commands and actions. The platform was deployed at the edge, enabling an analysis of the data closer to its sources. This resulted in a substantial acceleration of performance and reduced costs.

iguazio’s platform makes life simpler for developers. Simple, fast and secure – it accelerates the deployment of a variety of analytics services, eliminating data pipeline complexities and reducing time to insights. The system is enterprise grade and delivered as a fully integrated, easy to use appliance.