Edge computing

Complementing the cloud in IoT by enabling quick, secure, and local data processing

Learn about edge analytics

Edge computing: the perfect complement to the cloud in IoT

In many cases, it is simply not feasible to connect thousands or even millions of IoT devices directly to the cloud. This is where edge computing comes in: by facilitating data processing at the edge of a network – close to the source – it helps overcome some typical challenges of IoT deployments:

Sending huge amounts of data to the cloud can lead to high network costs for data transmission. In addition, high costs for cloud storage and processing can also accrue.
Latency can be an important consideration in IoT deployments. If it takes a long time for the cloud to process a request, this may well become an issue.

Use case overview

In many cases, it is simply not feasible to connect thousands or even millions of IoT devices directly to the cloud.
Edge computing facilitates data processing close to the source.
It therefore helps overcome network latency and enables companies to save costs.

How companies benefit from edge computing

With IoT devices generating ever-larger amounts of data, more and more companies are turning to edge computing as a way of processing that data quickly and reliably. What benefits does edge computing entail?

Overcoming network latency

Moving the processing of sensor data to an edge gateway is a way of avoiding network latency. This makes it a perfect fit for IoT applications that require sub-second response times – autonomous cars, for example.

Cutting costs

With edge computing, data can be filtered and processed before it is sent to the cloud. This reduces network costs for data transmission. It also reduces the costs for cloud storage and processing of data that is not relevant to the application.

Computational efficiency

Deploying analytics algorithms or machine-learning models to an edge gateway means that computational processing can be performed on smaller data sets. Edge computing is therefore an efficient way to process data.

Added device autonomy

Edge computing enables local storage and local computation. A device can therefore continue to function even if it is not connected to the network, thus improving the reliability of the entire IoT solution.

Improved security

Edge computing can reduce the number of sensors and actuators connected to the internet. This reduces the potential attack vector for security attacks.

Addressing privacy needs

Local data processing and filtering by an edge gateway can reduce the amount of sensitive and private information that is sent over a network.

Join our webinar

IoT Edge Computing 2020

Read our expert insights on edge analytics

Download

Bosch IoT Suite: enable your devices for AIoT

Bosch IoT Suite offers a fully integrated solution that brings custom logic directly where it is needed: on the device itself or on decentralized edge nodes. Our offering is designed to reduce complexity, costs, and latency. Configurable and reusable building blocks ensure the availability on platforms, require a minimum of integration work, and enable scalable applications. At the same time, machine learning, Artificial Intelligence and analytics are making it possible to extract more valuable information from data. Discover the unlimited possibilities to enable your devices for AIoT!

Your products for IoT edge and IoT edge analytics

Essential IoT enablement for edge devices: cloud connectivity, local messaging, software updates and container management

Bosch IoT Edge Agent

Extended device connectivity and advanced edge functions to manage IoT devices and data locally

Bosch IoT Edge Services

Our customers’ IoT projects

EnBW/SMIGHT implements IoT solutions with Bosch IoT Suite

How SMIGHT leverages the device management and IoT computing solutions from Bosch.

Hager: The role of standards in home energy management

The electricals company implements standardized EEBUS use cases with Bosch IoT Suite.