Mixed Reality Preparedness Platform (MRPP)
IN-PREP Mixed Reality Preparedness Platform is a user-friendly IT training platform for collaborative response planning. Our platform enables interagency training for the entire chain of command. In a training session, a simulated crisis is created and merged into the real world.
The IN-PREP MRPP
The MRPP provides an interactive visualisation of the crisis environment combining both simulated and real data. Features include:
- Decision support capabilities with built-in situational awareness
- Resource allocation in real time
- Rapid remote sensing for quicker response actions
- Large scale evacuation simulation
- Coordinated C2/C3 systems
- Vulnerability and Risk assessment
- Provides the capability to simulate pedestrian and vehicle-assisted evacuation scenarios while considering hazard propagation.
- Produces evacuation output data for preparedness and planning that augments information displayed on training and C2 platforms
The Evacuation Module provides insights on evacuation performance by simulating both pedestrian and vehicle evacuation processes. The module is capable of simulating the interactions between pedestrians and vehicles as well as the progressing hazard (wildfire, chemical spill, floodwaters) if such hazard is present in the modelled scenario.
The module produces a plethora of qualitative and quantitative data that highlight elements of the evacuation process including:
- Visual data: depiction of the pedestrian and vehicle movement over the modelled domain and evacuation performance graphs.
- Numerical data: overall evacuation times, time evacuees reached safe locations or target destinations, number of evacuees reaching target destinations, distance travelled, congestion experienced, the impact of hazards on population, number of evacuees being trapped and unable to evacuate.
The use of evacuation simulation allows the users to test and assess the validity of existing evacuation procedures by providing insights on how the evacuation process is likely to unfold. The users can also examine additional what-if scenarios, no matter how unlikely. These tasks are difficult or impossible to examine without the use of simulation tools.
The Evacuation Module is integrated with training and C2 platforms. The data that the module produces is displayed these platforms enabling trainees and crisis managers to better plan for, or to mitigate emergency incidents. This data augments the information displayed on the training and C2 platforms allowing for a fuller understanding of how the incident unfolds and how it can be mitigated allowing for informed decisions to be taken.
It supports descriptive details about individual attributes and vulnerabilities, which can support users in being reflexive and accountable with their assumptions about their local communities.
End-users can actively work with model designers to include relevant population characteristics in their risk management plans and by providing a socio-demographic breakdown of the population of interest to support the model in best representing the local communities for action.
- Digital training session management (from the creation to the evaluation)
- Digital collaborative preparedness & planning functionalities
Provides a digital environment for the training.
Information exchanged during the training are being recorded and displayed to the trainer allowing real-time follow-up of the training. Extended evaluation is also possible using recoded data, actions and automatically computed criteria (giving the level of collaboration for instance number of messages exchanged, number of units deployed, …).
The training platform features a Common Operational Picture (COP) sharing geo-localized and consolidated information at the strategic level. Multiple users and agencies can take part in the training physically or remotely sharing information in real-time.
The information displayed to the trainees comes transparently from the scenario, simulation models or other trainees, mixing reality and providing enriched training with situation and data hardly reproducible in regular training.
The training platform features a digital collaborative planning module, allowing the digital plan to be devised from multiple users and agencies. Section of plans can be shared and circulated between agencies to improve the collaborative response.
As a suite, a dedicated common login and authentication system has been designed to ensure GDPR compliance. It also supports controllers in demarcating different access restrictions and access logs.
They are designed multi-layered privacy settings that give the users control over what information is visible, and to whom. For example, a trainee has to opt into having a recording of their training sessions viewed by someone beyond an evaluator.
Proactive engagement with the various disaster risk resource categories and data standards used in these tools can support cross-border or cross-agency collaborators in better understanding each other’s different communication and planning needs.
Working with such platforms for planning and training can help users in identifying features that would be valuable for their collaborative protocols that support users on different sides of the borders better engage with each other’s different approaches to risk.
Use of the system has to come with user-defined protocols and revised duty-of-care for the digital shift. This should include organisational guidance that raises a user’s awareness of when privacy-risking activities could be taking place or where data processing agreements might be needed.
- Ability to visualize impact assessment estimates for different natural and man-made hazard scenarios.
- “Impact” is defined in terms of damage and/or economic loss to buildings and/or human casualties (injuries and fatalities).
- Results are displayed in map form on the MRPP interface.
Facilitates the improvement of the user’s situational awareness and ability to take better informed decisions regarding real-time planning, deployment and prioritization of resources to affected areas.
Provides risk and impact results as a range of answers to questions about what could happen were a hazard to unfold, supporting different perspectives on and approaches to risk within a single frame.
The “impact” measures considered within the model are defined in collaboration with end-users to they reflect the most important aspects of how users understand their communities.
The model behind this assessment is built upon an understanding that some sources of data may be affected by bias caused by social and economic factors, thus seeks to address the bias by combining several sources of data about a region.
Remote sensing (drone)
- Provision of virtual imagery using a drone simulation software and sensor simulation with multiple sensors, or live aerial images and videos with a drone and optical/infrared images and videos.
- Mission requests are received from C2s, a mission is planned and adapted depending on the equipment (drone/camera), and mission status and position is fed back to C2s.
- The setup is flexible and can be adapted to the needs and objectives of the exercise or demonstration.
Crisis managers can receive first sensor data within minutes and act accordingly.
Multiple entities can receive the sensor data at the same time which allows for a quicker assessment based on the same situational picture.
Minimal personnel and other resources are required for the deployment of the sensors and can be used for other collaborative actions.
The response can be planned more precisely and according to the real situation at the crisis area without delay in communication and endangerment of personnel.
No video footage is stored on the drones to support data protection of the public in training and exercises.
Tools to support drone privacy (e.g. https://dronerules.eu/en/) can support users in planning flights in ways that comply with local data protection recommendations.
Scenario Builder provides an intuitive and easy to use way along the appropriate environment for Trainers to abandon scenario-building using pen and paper and instead create in a fast manner draft digital scenarios that can be dynamically edited, modified, executed, re-played and stored. A scenario can be created based on historical or fictitious events, in detail to the second storyline that fully describes a realistic emergency crisis phenomenon. A vast variety of information can be included in each scenario such as actors, assets, events, incidents, events, agency messages, hazard parameters and social media posts. With scenario builder preparedness exercises can be repeated again and again, reducing the overall cost of training while increasing the participation.
- Dynamic scenario creation with adding and editing of injects
- Team drafting capabilities
- Modern UI with a timeline view
- Dynamic creation and editing-on-the-go capabilities of scenario incidents, events
- Detailed to the second scenario with data sources, exchanged messages among agencies and virtual social media posts
- Library of scenarios that can be saved and re-edited again later
- Ability to set scenario status at private or public mode
- Adding and editing scenario actors
- Adding and editing assets (human resources and equipment) on site
- Dynamic Time-plan management
- Run alternative evolutions of the scenario (Easy, Normal, Hard) or sub-scenario
- Scenario Import & Export functionalities
- Team sharing capabilities with access rights management
- Scenario versioning and history tracking
- Integration with Training Platform, C2s and Legacy systems through middleware
It is possible to include injects or models that do not fit expectations and includes categories for scenario elements not always considered by all agencies to encourage new forms of cultural awareness and as bias mitigation.
Watch how to build a scenario on the MRPP
Recommendation Engine is a Decision Support mechanism that collects previous lessons learnt, observations, experts’ opinions and historical data, and uses a set of intelligent algorithms (Fuzzy Logic, Knowledge Graphs and Neural Networks) to unravel correlations with scenario injects, issuing a series of recommendations for trainees across different agencies and command levels.
- Enhance decisions acting as a supportive checklist for trainees
- Issuing different recommendations across different command levels and agencies
- Enhance decision-making skills
- Issuing recommendations based on time-series prediction algorithm (e.g. Flood Level prediction)
- Issuing recommendations based on Social Medial Sentiment Analysis
- Social Media Sentiment Propagation for media crisis preparedness
- Semi-empirical Recommendation based on Knowledge Graphs
- Evacuation Decision based on Neural Networks
- Dynamic Asset Management based on Fuzzy Logic
- Full integrated with Scenario Builder working as one platform
- Integration with Training Platform and C2s through middleware
- Library of historical facts with lessons learned, experts opinion, observations
- Ability to import and export historical facts
- Make the Historical Fact status private or public
End-users are actively involved in the training of the Recommendation Engine, they can monitor algorithms as they are made in ways that let them understand what data is being used, how, and to what end
Each algorithm only covers the context of the OF and ensures that it does not overreach or learn false equivalencies.
A digital bracelet and connected mobile application to support paramedics during triage, collecting relevant data about the triage situation.
Can filter information to other systems, to ensure only relevant information is transferred.
To be used as a training device, volunteer consent and synthetic data can be substituted.
Designed to be GDPR compliant to support data subject rights.
For data protection, the default settings are for isolated and encrypted data transfer. However, a user can decide to configure them to transfer through a command and control or common information space.
Organisations can develop new digital ethics protocols to support best practices in the field.