GET IN TOUCH

Solving Questions and Providing Assistance for Maximum Efficiency

Frequently asked questions

Product
Rules-engine
Data security / Cyber security
Support
SaaS Subscription / Payment queries
Limitations of liability
Integration

The Acutro product is a stream intelligence platform that contains data aggregation, visualisation, and dashboard reporting components powered by a proprietary intelligent rules engine for logging and classification of events. It is a web-based application that utilises scalable cloud computing in AWS to execute ML/AI models to derive intelligent insights over large data volumes aligning with up-to-date enterprise architecture and data security requirements in the market.

It is data source agnostic, meaning that it can ingest data through multiple source types (i.e. direct integration, API, manual import). All mapped data sources are consolidated into a single master dataset on the Acutro Platform GUI to represent the connected building portfolio to drive the user experience. AI models include performance, utilisation and degradation over time, novelty, and outliers detection for significant events.

The Acutro interpretation of a smart building is one that can quickly and succinctly inform its asset owners or operators on its infrastructure performance, primarily in terms of energy efficiency and distribution, space utilisation, occupier comfort, and predictive / preventative maintenance.

o BMS or BAS integration
o EMS or Metering integration
o IoT integration
o Meteorological API integration
o CAFM/CMMS integration
o Asset Information Model or Asset Validation data ingest
o OEM data ingest
o Occupancy data ingest
o Integration of other control systems (HVAC/Lighting/Access Control/Lifts)

The Acutro rules-engine allows the end user to create single-condition or multi-condition logical rules against the dataset within the Acutro-hosted environment. Each individual rule is processed against the data as it is transacted inbound from the source, providing a mechanism to notify the user of an event when the conditions are met or breached. An event can be portrayed as an ‘alert’ or an ‘intervention’. This will drive engagement from the end user and its supply chain from the traffic of events created by the Acutro rules-engine.

Whilst it is dependent on the number of data sources and the volume of data being transacted, Acutro would typically connect your building online on its Platform within 3-4 weeks for a building up to 150,000 sq ft, up to 10,000 data points across 4 data sources.

Yes

The Acutro product is a stream intelligence platform that contains data aggregation, visualisation, and dashboard reporting components powered by a proprietary intelligent rules engine for logging and classification of events. It is a web-based application that utilises scalable cloud computing in AWS to execute ML/AI models to derive intelligent insights over large data volumes aligning with up-to-date enterprise architecture and data security requirements in the market.

It is data source agnostic, meaning that it can ingest data through multiple source types (i.e. direct integration, API, manual import). All mapped data sources are consolidated into a single master dataset on the Acutro Platform GUI to represent the connected building portfolio to drive the user experience. AI models include performance, utilisation and degradation over time, novelty, and outliers detection for significant events.

Acutro can communicate notifications of events from the Platform via Email, SMS, Text-to-Speech, Microsoft Teams.

Yes, Acutro deploys commodity AI/ML components across the Platform.

Multi Factor Authentication is used for all support access. SSO is not available as standard, but this can be implemented upon request by any customer. This will become a default setting in 2024 Q3/Q4.

As Acutro utilises AWS as the primary cloud technology, it can take advantage of the security certifications that AWS holds for specific standards, including ISO27001:2013 for how it controls and manages the security of the software application. This is supplemented by Acutro holding its own ISO27001 accreditation and performing regular pen testing of the application by a reputable 3rd party consultant every 6 months. For further questions around this please contact our support technical@acutro.co.uk.

All building data that is hosted on the Acutro Platform belongs to the customer, or an appointed service provider who manages the built environment that Acutro is monitoring.

Acutro has invested in technical, physical and administrative safeguards to do its part to help keep your data safe and secure. Acutro deploys appropriate monitoring technologies that will notify you if there appears to be unauthorised access to your account and it may restrict access to certain parts of the services until access is verified by an authorised user.

Examples of security safeguards we have in place are: The Acutro Platform has been externally verified by 3rd party penetration testing. Acutro Support is based on RBAC (Role-Based Access Controls). Multi-factor authentication is used for all support access. All Support actions are logged with full history. Acutro is underpinned by AWS using industry best practices and some of the highest security standards globally.

Data is represented across various regions depending on the data sovereignty of the customer. The data can reside in any geographic locations subject to understanding the specific customer requirements around data security.

UK & India

The Acutro Platform standard Service Levels are: 6 hour response on all support tickets. Online Support 24 x 7. System Availability 99.9%. Enhanced support response times are available for Enterprise customers.

Yes, Acutro works to monthly product releases. All feature requests can be sent to technical@acutro.co.uk and Acutro will provide a response with 5 working days to confirm if this is being considered and advise on next steps.

Acutro customers pay a one-off mobilisation fee, then an annual subscription fee to use the Acutro platform. Acutro provides a standard subscription agreement that sets out the service you can expect from us, the ownership of your data and how Acutro protects it, as well as the commercial and financial terms. There is a minimum subscription period of 12 months.

Please see example pricing below for a 100,000 sq. ft property with 250 assets being monitored.

No, there are no limitations on the volume of data that can be handled. Acutro is licensed against the quantity of buildings or assets within scope for the selected Acutro service purchased.

After an Acutro subscription is ended, cancelled or terminated, the building data will be held for up to 60 days. In order to access this data, you must contact Acutro support to request an export of all data. The customer’s building data will be shared at no additional cost.

Please contact technical@acutro.co.uk for further information on this.

Yes, API documentation can be made available upon request.

Didn't find what you're looking for?

Glossary

TERM

DEFINITION

Weather Normalised Energy Consumption

Weather normalisation is a process that adjusts actual energy consumption or peak outcomes to what a building would have used under average conditions. The weather in a given year may be much hotter or colder than your buildings normal climate; weather-normalised energy accounts for this difference.

Data Abstraction Layer

Acutro deploys a data abstraction layer in order to reduce a particular body of data to a simplified representation of the whole. Abstraction, in general, is the process of removing characteristics from multiple sources of data and condensing it to a set of essential elements that are user-friendly to the relevant stakeholders.

Asset Validation data

The Asset Validation data is typically a condition survey report produced by a stakeholder across the property ecosystem that captures the entire asset register, including key data values like asset group, system group, manufacturer, model, serial number, install date, location, human survey condition, maintenance schedule information, forecasted lifecycle costs etc.

IAQ

Indoor Air Quality is the air quality within and around buildings and structures. IAQ is known to affect the health, comfort, and well-being of building occupants. IAQ is evaluated through collection of air samples, monitoring human exposure to pollutants, analysis of building surfaces, and computer modelling of air flow inside buildings. IAQ is part of indoor environmental quality (IEQ), along with other factors that exert an influence on physical and psychological aspects of life indoors (e.g., lighting, visual quality, acoustics, and thermal comfort).

Predictive Maintenance

Predictive maintenance (PdM) is a technique that uses data analysis tools and techniques to detect anomalies in your operation and possible defects in equipment and processes so you can fix them before they result in failure. Ideally, predictive maintenance allows the maintenance frequency to be as low as possible to prevent unplanned reactive maintenance, without incurring costs associated with doing too much preventive maintenance.

IoT data

The internet of things, or IoT, is a system of interrelated computing devices, mechanical and digital machines, objects, animals or people that are provided with unique identifiers (UIDs) and the ability to transfer data over a network without requiring human-to-human or human-to-computer interaction.

Data Source

A data source may be the initial location where data is born or where physical information is first digitized, however even the most refined data may serve as a source, as long as another process accesses and utilises it. Concretely, a data source may be a database, a flat file, live measurements from physical devices, scraped web data, or any of the myriad static and streaming data services which abound across the internet.

Telemetry

Telemetry is the automatic recording and transmission of data from remote or inaccessible sources to an IT system in a different location for monitoring and analysis. Generally, telemetry works through sensors at the remote source which measures physical (such as precipitation, pressure or temperature) or electrical (power draw) data. This is converted to electrical voltages that are combined with timing data. They form a data stream that is transmitted over a wireless medium, wired or a combination of both.

BMS data

A building management system (BMS) is a control system that can be used to monitor and manage the mechanical, electrical and electromechanical services in a facility. Such services can include power, heating, ventilation, air-conditioning, physical access control, pumping stations, elevators and lights. The data monitored on the BMS is largely telemetry and binary values capturing the operating profile of all critical assets across the base build infrastructure of the property.

Degradation ML Model

Long Short-Term Memory (LSTM) is a type of recurrent neural network (RNN) architecture that is designed to capture and predict patterns in sequential data. The data streaming from the BMS systems and IoT sensors is relatively simple but the patterns and subtle variances from the individual data points builds a comprehensive picture into asset operation performance and the indicative signs of degradation or potential failure. The LSTM approach allows the platform to indicate potential issues before they would be identified with traditional engineering.

Novelty Detection ML Model

A Support Vector Machine (SVM) approach added another mechanism through which these ‘outlier’ events could be identified through novelty detection. It is an adapted model which involves identifying instances that significantly differ from the majority of data points in a dataset. This is also known as one-class classification or one-class SVM. The goal is to build a model that can accurately identify instances that are unusual or novel compared to the majority of the data. These novel instances might represent anomalies, outliers, or rare events. In the example discussed this would look for the difference in airflow on a smaller time period not a degradation but more of a big bang critical event or failure. The outcome of the combination of approaches now allows alerts and interventions to be driven from almost any scenario presented in the data which would have an impact on the end client.

Alerts

As part of the IoE architecture; an alert is triggered from the IoE rules-engine providing a notification to the specified user group with a specified message that will require action on the Platform. Alerts can be received by email, SMS, Text-to-speech, or API.

PPM minutes

The annual timings allocated to the asset ID against the adopted maintenance standard.

Meteorological data

Historical and forecasted Meteorological data pertaining to the atmosphere, such as wind, temperature, air density, visibility, precipitation levels and current weather condition.

Rules

A core component on the IoE Platform that allows you to define rules and then apply those rules to data. The rules that are defined and stored can trigger alert notifications to the specified user group with a specified message that will require action on the Platform.

Building Data

This page component on the IoE pre-aggregates all asset records and their associated telemetry values against a time series data base allowing the user to visualise, plot, overlay, interrogate, trend, share and export data.

Asset Health AI

This is providing a dynamic score as a % that renders a RAG status indicator every 7 days from AI models applied against the dataset which is considering data from multiple sources (primarily telemetry points from BMS, IoT, and meteorological sources) in relation to that asset’s operating profile against its baseline. To provide an Asset Health score, the AI model requires at least over 5 telemetry points across at least two data sources to provide the foundation of an asset health score. The more datapoints and sources factored into the AI model, the more accurate the Asset Health score will be. The Asset Health AI scores will the workflows on maintenance activities relating to suppression of tasks or acceleration of tasks - ultimately a more dynamic, data-led maintenance model.

Asset

With respect to maintenance, an asset is any piece of equipment, property, or other physical item used in a facility's operations.

Maintenance Suppression

The execution of opting not to perform an upcoming PPM task in the calendar based on the Asset Health AI score powered by the Acutro IoE Platform.

Intervention

A gentleman from New York discovered what he calls an “oversight” on the part of 99.9% of all marketers that allows him to get otherwise paid-for advertising at Google as well as all other search engines that allow sponsored ads.

Free scale-assist for when you need more resources;

Defined on Acutro IoE as a manual intervention task mapped against any asset / system / building for a specific use case. Must be approved or declined by an administrator user to be logged and performed.

PPM

Planned preventative maintenance (PPM), also commonly referred to as planned maintenance or scheduled maintenance, is essentially a scheduled maintenance routine for the assets across an estate. Tasks are scheduled ahead of time, while assets are still in functioning order.

Contacting the Acutro team

Contact our team of experts today to learn how Acutro can transform your property performance. Whether it's meeting sustainability targets, reducing costs or you're simply curious about our revolutionary technology, we are happy to help.
hello@acutro.co.uk
0333 577 2019
Acutro HQ, London

CHANGING BUILDINGS BY BUILDING CHANGE

Privacy Policy
Terms
© 2023 - All reserved
cross