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What is DataCurrent?

The real-time observation of rainfall using rain gauges allows operations teams to swiftly recognize possible flooding or sewer overflow incidents. By meticulously monitoring and analyzing precipitation levels across multiple locations, one can estimate rainfall in regions that lack direct measurement, employing the technique known as “Distributed Rainfall Modelling Technique” (DRMT). Moreover, merging rainfall radar data with rain gauge measurements enhances the creation of detailed rainfall coverage maps. Analyzing historical rainfall statistics also aids in developing rainfall intensity-duration curves, which can be matched against the region's design intensity-duration-frequency curves, facilitating the determination of return periods for significant events through forensic examination. Additionally, new intensity-duration-frequency curves can be established, influencing the design of essential drainage infrastructure such as sewers, channels, and storage systems. The ongoing analysis of flow data, in conjunction with rainfall information, leads to the formation of rainfall versus stormwater runoff response curves, which play a crucial role in accurately calibrating drainage models. This thorough methodology guarantees that urban planning and flood management initiatives are not only informed but also adapt effectively to real-time environmental conditions, ultimately enhancing community resilience to extreme weather events.

What is AWS IoT Analytics?

The information produced by IoT devices is largely unstructured, which poses significant difficulties for conventional analytics and business intelligence systems that are designed primarily for structured data. These devices collect data from various noisy environments, such as temperature fluctuations, motion detection, and sound levels, resulting in common problems like data gaps, message corruption, and unreliable readings that require extensive cleaning prior to any substantial analysis. Moreover, the value of IoT data often hinges on its integration with external data sources from third parties. For example, irrigation systems in vineyards can improve moisture sensor readings through the inclusion of rainfall data, allowing farmers to refine their water use and boost crop productivity effectively. To facilitate the analysis of data generated by IoT devices, AWS IoT Analytics simplifies each intricate step in the process. This fully managed service operates on a pay-as-you-go basis, allowing it to effortlessly scale to accommodate varying requirements while also streamlining the overall data analysis procedure. By utilizing such automated solutions, companies can more effectively extract critical insights from their IoT data, ultimately leading to better decision-making and improved operational efficiency. In this way, organizations can harness the potential of their IoT investments to drive innovation and growth.

Media

Media

Integrations Supported

Integrations Supported

AWS App Mesh
AWS IAM Identity Center
Oracle Database@AWS

API Availability

API Availability

Pricing Information

Pricing not provided

Pricing Information

$3.43 per month

Supported Platforms

SaaS

Supported Platforms

SaaS

Customer Service / Support

Standard Support
Web-Based Support

Customer Service / Support

Standard Support
Web-Based Support

Training Options

Not specified

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

Smart City Water

Company Location

Canada

Company Website

smartcitywater.ca/datacurrent/

Company Facts

Organization Name

Amazon Web Services

Date Founded

2006

Company Location

United States

Company Website

aws.amazon.com/iot-analytics/

Categories and Features

Data Virtualization

Not specified

Categories and Features

Asset Tracking

Not specified

EAM

Not specified

Equipment Maintenance

Not specified

IoT Analytics

Not specified

IT Asset Management

Not specified

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