Really pleased to be selected for the Wessex Water Proof of Concept looking at making smarter use of EDM data. Our MAP Rain solution has been chosen as one of three solutions to be trialed during the 3 month Proof of Concept. This follows a rigorous review of competition entries from 30 companies.
Summary of a case study with Leeds City Council for alerting and reporting during Storm Ciara using our MAP Rain real-time rainfall analytics solutions. Leeds City Council use MAP Rain to analyse historic rain events and to receive forecast rain alerts for catchments and points of interest. This case study reviews the alerts generated for storm Ciara on the 9th and 10th February 2020 and compares the actual rainfall results against the alerts generated.
The upgrade to the Meniscus Calculation Engine (MCE) on our free-to-use Home Energy platform lets users create their own dashboards. This will let us phase out the old Silverlight dashboard that requires Internet Explorer. Users can create their own widgets and embed them in their own HTML dashboard in a matter of minutes. The dashboard will then automatically refresh every time you open it and at the refresh rate you entered when you created them.
MAP IoT Entities give you control over the analytics deployed in your IoT application as well as the ability to replicate to tens of thousands of instances. It simplifies the job or turning any type of raw data into the analytics and metrics you want to display to your users. MAP does all the plumbing so you just need to upload raw data and pull down the calculated metrics.
New MAP IoT Gateway lets users connect to the MAP servers directly from their device allowing two way control via a dashboard
New MAP Rain alert dashboard makes it much easier to keep track of forecast rain alerts for Points and Polygons in your area of interest. The alert dashboard updates every 5 minutes, as new rainfall data arrives, and updates the colour of your Points and Polygons depending on the level of flood risk. The alert dashboard also displays an animation of the forecast rainfall across the UK
MAP uses the principle of lazy loading to ensure that only the data required to calculate a data set is extracted from the database. This speeds up the processing and calculation of data and helps MAP deliver it’s lighting fast calculation times
MAP allows users to create their own data types which can greatly improve and speed up the processing of more complex data and provides the flexibility to process any type of data
MAP uses a dynamically constructed dependency tree to identify the relationship of Items and to determine which Items (s) need to be calculated in order for another Item to be calculated.
Meniscus Analytics Platform (MAP) uses Data Blocks and Data Versioning to reduce disk IOPS and deliver the calculation speeds for real time analytics – view the article to see more information