EOP-LABS

Objectives of the Product

Satellite space missions’ development has increased in the last years. Apart from all the complexity of the development of the space segment, it is crucial that adequate processing instruments exist on ground. Ones that are flexible enough to serve any mission regardless of size and complexity, with minimum to none need of tailoring and that can be easily accessible by clients of all sizes.

This EOP-LABS project will make GMV Prodigi available through the AWS Marketplace. GMV Prodigi is a Payload Data Ground Segment (PDGS) service that clients can procure without any third-party intervention, including the cloud processing capacity dimensioned for their needs, and set up the processing chain as they see fit.

Users will be able to insert and test their own image processors in a “plug and play” way, allowing a better time to market.

Customers and their Needs

From the GMV experience and contacts with target customers, the main needs and suggestions for improvements are:

Automating service provision
Reducing the time to market of imagery products (First-mover advantage)
Managing large amounts of data in processing and dissemination.
Being ready to cope with changes in the mission configuration.
Accessing a processing platform without the costs and time-consuming hardware procurement or complex setups.
Accessing EO processing infrastructures in a standalone mode, without the need to establish third party agreements.

These needs are common to every target customer identified.

In this activity, GMV will count with the involvement of two users – a satellite manufacturer and a satellite operator/provider of EO services – that will provide real data for comparison and critically analyse the performance of GMV Prodigi running from the AWS Marketplace and servers.

Targeted customer/users countries

The target customers, at least for the first stages of commercialisation, will be European. However, due to the global nature of the service to be provided, customers are expected to be from any country. The identified customer segments are:

Satellite operators
Satellite manufacturers that develop their own instrument data processing chains
Ground-segment operators
EO service providers
The EO scientific community

Product description

This will be the first automated, self-contained PDGS service available online for any users.

With this, users will be released of the PDGS service procurement and the need of extensive hardware procurement and configuration, allowing a better focus on the core activities of satellite imagery production and exploitation.

GMV Prodigi is not dedicated to the implementation of the image processors but allows an easy process to install, test and run multiple processors to the user.

GMV Prodigi will be available in the AWS Marketplace. Users can download it and the configuration of the processing power will be secured, according to the needs of the mission, during the installation process.
Users can then plug their image processors through a simple API and configure the desired processing chain.
Then, the processing is secured on the cloud-based network configured at installation and the users will receive the processing data at the desired location.

Added Value

Traditional mission ground segment developments undergo multiple steps, some of which are not contributing to the final goal of the mission, which is the provision of added value products.

EOP-LABS will remove or facilitate some of the steps. This will translate in products’ time savings to market and a decrease in complexity and costs during the implementation.

When users intend to acquire a processing chain, either they develop it in-house or buy existing solutions. Typically, these solutions must be highly tailored to the mission needs, hence being “locked” to the mission initial configuration. This always implies a procurement and negotiation process for the PDGS acquisition.

The EOP-LABS approach will remove the need for this procurement. GMV Prodigi will be accessible to any user, who can acquire it directly from the AWS Marketplace, according to the price schemes proposed and have it ready for usage once installed.

Since the processing capabilities are fully cloud-based, the HM procurement is removed as is the need to configure and maintain it. Integration of the image processors is also a simple feature. They can be “dropped” in GMV Prodigi, replaced and tested with simple procedures and configuration of the chain.

Current Status

GMV has secured the ‘AWS Partner’ status and is currently deploying the base version of GMV Prodigi with the current installation procedures in AWS servers, the same environment where it is supposed to be used by the clients. Once it is fully functional, the next step will be the development of the installation package that will automate the installation of GMV Prodigi.

In parallel, the preparation for AWS verification procedures for a Marketplace app is ongoing.

SkyRider

Objectives of the Product

The STRATOSYST’s HAPS for Earth Observation project has been focusing on aligning our platform with user needs. Through market surveys and user interviews, we identified key requirements such as high-resolution, continuous monitoring, all-weather performance, and real-time data delivery. These insights are shaping our development approach, ensuring that SkyRider meets the demands of the addressed sectors.

A key outcome of this phase is a potential development partnership with a data processing company, where SkyRider’s data processing will be tested in real-world conditions. On the technical front, we’ve finalised the foundations for the Digital Twin and CFD analysis, collaborating with key partners to ensure the platform’s readiness. Moving forward, these learnings and milestones will guide the next phases of SkyRider’s development, keeping user-driven innovation at the core of our efforts.

Customers and their Needs

The target customers for STRATOSYST’s SkyRider HAPS platform include data processing companies, environmental monitoring agencies, disaster management organizations, and industries requiring continuous, high-resolution EO data. These users need real-time, persistent data for applications such as environmental monitoring, disaster response, and resource optimisation.
Existing satellite systems, while useful, often fail to deliver the required high- resolution data and frequent revisit rates, with high costs and temporal limitations. Drones and aircrafts, while alternatives, lack the ability for long-term or remote monitoring.

SkyRider addresses these challenges by providing continuous, flexible, and high- quality data collection. Over 130 potential users were identified, and seven comprehensive interviews were conducted to ensure alignment with customer needs. Key requirements such as all-weather performance, continuous monitoring, and real-time data processing have been integrated into SkyRider’s development. This user-driven approach ensures that the platform meets the specific needs of its target sectors, offering a cost-effective and adaptable solution for the evolving demands of EO customers.

Targeted customer/users countries

The majority of the initial targeted customers for STRATOSYST’s SkyRider HAPS platform are located in Europe and North America. These regions, with their established EO markets and demand for advanced data solutions, are key focus areas for the platform’s early adoption.

Product description

SkyRider HAPS is a Lighter-Than-Air vehicle with a 30 kg payload capacity, designed for year-round stratospheric operations. Unlike space-based platforms, SkyRider operates in the stratosphere, providing imaging data continuously. Its stratospheric segment includes seven key subsystems: buoyancy, structure, propulsion, safety, power, electronics, and communication. Equipped with station- keeping capabilities, SkyRider hovers persistently over any location on Earth, offering uninterrupted service for scientific and commercial applications. Propulsion is powered by solar panels, enabling efficient navigation through stratospheric winds. The ground segment features a mobile discharge ramp, communication antenna, and control system, all compactly stored in a standard ISO container for easy transport.

***Preliminary HAPS stratospheric segment design***

Added Value

The STRATOSYST’s SkyRider HAPS platform offers distinct advantages over traditional EO methods such as satellites, drones, and aircrafts. Satellites provide broad coverage but are limited by high costs, lower resolution, and infrequent revisit times, making them less suitable for continuous, localized monitoring. Drones and aircrafts offer better resolution but lack the endurance and cost-efficiency needed for long-term or remote operations.

SkyRider addresses these gaps by delivering persistent, high-resolution data over specific areas at lower operational costs and without environmental impact. Operating in the stratosphere, SkyRider enables continuous monitoring with minimal latency, overcoming the limitations of satellites and aircrafts. This makes it ideal for real-time, localised applications like environmental monitoring, disaster response, and secure communications. Additionally, SkyRider integrates seamlessly with the existing EO infrastructure, complementing satellite data by providing higher resolution and reducing latency. Its all-weather capability and extended operational time make it uniquely valuable to sectors that require reliable, high-quality data over-extended periods.
SkyRider thus brings unmatched flexibility and persistence to meet evolving data needs.

Current Status

During the first six months, STRATOSYST focused on customer identification and outreach, conducting over 130 contacts and six detailed interviews to refine the SkyRider HAPS platform. The activity was promoted at international events like Eurosatory and Collision, leading to discussions with potential partners, such as flight planning or data processing companies. Additionally, STRATOSYST introduced the HAPS for EO solution to commerce diplomats from wildfire-prone countries.
Negotiations with key companies are ongoing. The next steps include formalising business opportunities based on customer insights and preparing for a following design and development phase.

The Golden Twins

Objectives of the Product

The Golden Twins platform addresses critical challenges faced by the tourism, maritime, and insurance sectors in Greek islands, offering real-time monitoring and risk management for forest fires, extreme weather events, and vessel activity. Key problems include the need for rapid detection and response to forest fires, timely alerts for extreme precipitation events and post event monitoring such as floods and debris flow, and comprehensive vessel tracking even in areas with limited AIS data.

To solve these issues, Golden Twins leverages data from Greek CubeSat missions, Sentinel satellites, and Copernicus contributing missions, in order to provide standardised, real-time insights and risk assessments for fire prevention, extreme weather damage monitoring, and maritime safety.

By offering a system-agnostic, multi-mission hosting platform built on open standards, the Golden Twins platform aims to bridge the gap in the national space program and serve as a competitive, low-cost solution for the emerging EO market.

Customers and their Needs

The Golden Twins platform targets customers in the tourism, maritime, and insurance sectors, specifically focusing on businesses operating on Greek islands. Key users include hotel management companies, maritime operators, and insurance firms, who all have the need for safety alerts, evacuation guidance, and risk assessments.

In tourism, the need is for real-time monitoring of forest fires and extreme weather events, providing safety alerts, evacuation guidance, and post-event damage assessments to protect tourists and properties. In the maritime sector, customers require vessel monitoring services, even for ships with limited AIS data, to ensure maritime safety, prevent illegal activities, and manage port congestion. The insurance sector seeks accurate and timely data for risk assessment and to expedite claims processing for natural disasters like fires and floods.

A number of users representing each of the sectors above actively participate as pilot users throughout the project, providing feedback through questionnaires and workshops regarding the platform’s functionalities, as well as guiding development through sprint reviews and participating in the verification and validation activities of services, the platform’s UI/UX, and the overall system.

Challenges include delivering high-resolution, real-time data for precise monitoring and rapid response, while ensuring seamless integration of LEO satellite missions and future micro-satellites to meet the growing demands for accurate, location-specific insights.

Targeted customer/users countries

The Golden Twins platform provides a platform integrating several services
for monitoring islands. The starting case studies include Greece, with a possible launch in remote islands of the world in the future, where launching CubeSats might have a lower cost than acquiring commercial satellite data.

Product description

The Golden Twins is an advanced EO platform combining high-resolution data from CubeSats and open-access sources like Copernicus. It offers near real-time monitoring for sectors such as tourism, maritime, insurance, and environmental management.

The platform’s innovation lies in its high revisit rate (multiple times daily) and spatial resolution (1-10m), combined with AI-driven analytics and data fusion techniques. Services include rapid and accurate fire danger assessments, real-time fire monitoring, and detailed post-fire mapping; extreme precipitation events monitoring by reporting (alert, maps, plans) of floods with assessment of any subsequent debris flow and /or infrastructure damage; and vessel tracking using multiple data sources (SAR and multispectral data, AIS), providing rapid and accurate insights.

Users access the platform via a web-based interface to track incidents, generate reports, and receive customised alerts. The Golden Twins platform is scalable, cost-effective, and designed for adaptability, making it ideal for various commercial applications and operational requirements.

The Golden Twins platform consists of five (5) main components, also seen in the presented system architecture below. The main components of the platform product are:

UI & Reporting Module (C3):.
Data collection (C1)
“Processing engine” (C2) module consisting of the three (3) EO services as separate components (C2a, C2b, C2c)

Added Value

The Golden Twins platform offers significant advantages over competitors by integrating widely used open EO data with data from CubeSat missions, leveraging their high revisit frequency and spatial resolution. This results in faster, more accurate monitoring for the three delivered services which monitor forest fires, extreme precipitation events, and vessel activities. Additionally, Golden Twins shall act as the first comprehensive commercial solution in Greece, serving commercial sectors such as tourism, insurance, and maritime, unlike government-focused competitors. Its scalable, cost-effective solution, using low-cost satellite missions, ensures widespread applicability, especially for remote islands. The potential to include future CubeSat missions can further enhance these traits and add more services. The platform’s AI-driven real-time analysis, combined with advanced data fusion techniques, further distinguishes it from traditional methods.

Current Status

The Golden Twins activity kicked off in September, initiating the first 6-month cycle. The focus is currently on user requirements definition, with ongoing engagement with key stakeholders from tourism, maritime, and insurance sectors to gather feedback and define technical specifications. Initial work has begun on data collection and service prototypes. Stakeholder interviews, surveys, and user story mapping are being conducted to refine user experience and align with project goals. Upcoming activities include pre-deployment testing and the further development of data processing pipelines for each service. The activity is on track, with early feedback helping shape the development process.

SMEaaS

Objectives of the Product

How can product companies find a golden middle between satisfying the customer by delivering rapidly the product, based on customer expectations, and securing a high rate of product purchases?

One of the main problems in the space industry is late access to hardware that leads to incomplete testing and validation of the software. Facing this issue, KP Labs has come up with a solution on how to fulfil the needs of the customer and secure income, by allowing the client to have a rapid remote access to its hardware products and creating SME as a Service solution. Solving this problem will satisfy both customer and the manufacturer by giving the following:

For the Customer:

Ability to get acquainted with the product by remotely accessing it, right after the payment for the subscription and test several configurations to select the relevant one before the purchase of a physical hardware.
Shortening the lead time of the test solution from several months to a few minutes.
Making the smart investment in the right solution.
Develop software or algorithms for their mission in parallel with procurement of the hardware.

For KP Labs:

Securing that customer will stay and test the solution.
Saving time and resources for the contractual part, as a customer is specifying the wanted product through the system.
Raising the probability of the purchase after the initial product testing.
Delivering an added value for the customer, which is not available within the competition, thus building a strong brand in the market.

Customers and their Needs

Targeted customers include companies and institutions from space industry who use algorithms (traditional and AI/ML) on satellites and want to test their solution before utilisation in space. Quick access to hardware and possibility of verification of code is one of their main needs, and KP Labs’ SMEaaS will meet it.

Targeted customer/users countries

Worldwide.

Product description

KP Labs would like to propose a new way of selling upstream DPUs, by giving the customer rapid remote access and introducing hardware as a virtual service.

KP Labs has a portfolio of products called Smart Mission Ecosystem:.

It consists of several products:

Modular on-board software (Oryx);
Three different Data Processing Units (Antelope, Leopard and Lion);
A set of AI algorithms (The Herd) and EGSE (Oasis).

These products define the company product offer and are dedicated for missions up to 500 kg, and up to Class 4. The major idea of SME as a Service is to allow customer to use them remotely, whenever they want and wherever they are. The Customer will get access to the major KP Labs hardware products to be able to test and verify their algorithms. This solution will allow the customer to receive remote access to the product through Virtual Private Network as presented below, and use it as they pay, being able to configure the solution as they need. To use the SME as a Service, a customer will need a computer station with open-source tools to design their AI solutions (such as TensorFlow), list of requirements for the mission and Internet access.

Added Value

Currently, the most popular way of testing algorithms on the real hardware requires purchase of the hardware and waiting for it to be produced and delivered. It is hard to test and experiment with the data processing units, and choosing the one that really meets the actual mission’s needs. Utilisation of SMEaSS allows testing and verifying code on different units of hardware, which in turn allows to choose between them, according to the specific solution’s needs.

Current Status

MTR Milestone has been achieved and all due deliverables accepted by ESA. While the project is halfway to completion, it is a big milestone since the Customer Dashboard is now completed and managed by KP Labs. Next steps would include Client Zero engagement for the testing of the service. Hardware production is in progress – aiming for 3 units of Antelope and 4-5 units of Leopard by no earlier than June 2024.

Irreo Platform

Objectives of the Product

Irreo aims at enabling growers to automate their irrigation systems in an intelligent and efficient way to mitigate drought problems caused by ongoing climate change, a factor that has made irrigation an increasingly delicate and complex process to manage. However, to cope with this, growers increasingly tend to use technological solutions that present certain critical issues:

soil moisture sensors are very expensive and provide only one-point data to make irrigation decisions, resulting in non-uniform production throughout the plot;
growers spend time converting the provided irrigation advice into an actual irrigation planning;
growers spend time to modify the irrigation schedules on their controllers to follow the elaborated irrigation planning.

Incorrect use of technological solutions can lead to inefficient irrigation, thus wasting water and energy and reaching high operating costs, but also to poor harvest and risks for crop survival.

In view of all this, the Irreo platform uses satellite data, AI and automation to

provide crop water requirements without the need to buy, install and maintain sensors;
provide an optimal irrigation scheduling that dynamically adapts to weather and crop water requirements, while considering irrigation system constraints and agronomic strategy;
the irrigation plan is automatically downloaded to our controllers to perform variable rate irrigation.

Customers and their Needs

The Irreo platform was conceived and designed particularly for farms growing crops irrigated by drip irrigation systems. Growers and all professionals who support them in the management of the crop irrigation process are our main target customers: these people have a great responsibility, as irrigation is among the activities that most affect the quality and quantity of the harvest, especially for certain types of crops. Moreover, often poorly managed irrigation can mean waste of water and energy, higher costs or even serious damage to the crop or its total loss. The implications of climate change have made the situation even more complicated.

As the main objective of the customer is to cultivate the crop in the best possible way, given that this is directly linked to the profitability of the farm, the grower needs to optimise irrigation:

deciding when and how much to irrigate precisely and affordably;
scheduling daily irrigation automatically and dynamically;
relying on an irrigation decision support system connected to the automation system controlling the irrigation plant;
relying on a tool to understand how the crop is growing and whether there are any problems

Targeted customer/users countries

Italy, Spain, Portugal, France, Morocco and Turkey.

Product description

The Irreo platform is an advanced irrigation system that combines the potential of modern satellite observation technology, AI and automation to increase crop yield through improved water efficiency, resulting in reduced irrigation costs.

The platform consists of three main modules:

Satellite-based crop water requirements: Irreo uses different satellite data and machine learning algorithms to estimate the actual evapotranspiration of different types of crops, with a high spatial resolution and a daily revisit time, without the need to buy, install and maintain any soil moisture sensors on the field.
Optimal irrigation scheduling: Irreo provides optimal and dynamic irrigation scheduling, recommending when and how much to irrigate for each sector, taking into account the water requirements of the farm’s crops, the constraints of the irrigation system, and the grower’s agronomic strategies.
Variable rate (or dynamic) irrigation: the optimal irrigation scheduling elaborated by Irreo is automatically downloaded to our controllers to perform variable rate irrigation on each sector, managing solenoid valves, fertilizers, mixers, pumps, filters and alarms. Using our controllers, our users will have the ability to dynamically irrigate each sector of their plot in fully automatic manners and manage the entire irrigation process remotely from our app.

Added Value

To cultivate the crop in the best way, the grower needs to optimally manage irrigation.
Nowadays, (s)he monitors growth and health of crops and decides when and how much to irrigate every field sector relying on experience or sensor technology.
The first scenario presents several risk variables and takes time, while the second one is expensive, time-consuming and risks to be economically disadvantageous, thus leading to incorrect use of technology, with consequences on the yield.
Once (s)he has collected data, it is time to translate them into a realistic and efficient irrigation plan and then start it manually or set the various schedules via the automation system. These operations should be done every day and are not risk-free.
With Irreo, the grower constantly receives precise and useful data on the app and can rely on an optimal irrigation plan that dynamically adapts to weather and crop water requirements, while considering irrigation system constraints and agronomic strategy, and that is automatically transferred to the irrigation system through our controllers.

Irreo’s innovations imply:

time savings, as the grower needs some minutes per day to optimally manage irrigation;
a 16% increase in water saving.
30 mm more evapotranspiration in the season with an estimated 11% increase in yield.

Current Status

The project kick-off was held in July 2024, and the preparation of the requirements review has been completed.

INSIGHT4EO

Objectives of the Product

Traditional EO satellites lack on-board data processing, relying on ground-based chains for data acquisition, causing bottlenecks in timely product generation. Our goal is to resolve this by revolutionising data handling and processing.

Customers face dilemmas regarding inefficient data acquisition, high costs, and ineffective utilisation of acquired data. Insight4EO aims to provide an innovative solution by leveraging satellite constellations and advanced analytics to enhance spatial/temporal resolution while reducing reliance on traditional, costly data download approaches. This solution streamlines the data pipeline, optimising the delivery of actionable insights while minimising unnecessary data transfer.

The key focus is maximising Return on Investment (ROI) for EO missions by prioritising valuable data. We intend to create a platform that distinguishes valuable data in real-time, facilitating immediate utilisation of critical information (e.g., real-time emergencies) and efficient cataloguing for change detection. Our approach involves redefining data handling methods to ensure that only relevant, valuable data are processed and transmitted, meeting varied user needs efficiently. Through this, Insight4EO aims to empower users with cost-effective, timely, and actionable EO products.

Customers and their Needs

The space industry is always looking for innovative products and developments that provide efficient solutions, which reduce cost, effort and improve the result, among other needs, such as:

Reach goals of EO missions within budget limitations
Improve capabilities of national / European EO industry
Maximise amount of useful data received from EO satellites
Maximise returns of EO satellites
Minimise time from tasking order to receiving useful data from satellite
Maximise amount of useful data received from EO satellites
Minimise cost of operations
Improve value proposition of EO satellite systems

Targeted customer/users countries

Insight4EO serves diverse customer segments in Earth Observation (EO):

Institutional Customers: Government-linked bodies, public entities, and non- profits sponsor missions for scientific or organisational goals within limited budgets, seeking risk mitigation and industry support.
Commercial EO Satellite Operators: Private entities aim to maximise revenue and minimise costs. Insight4EO enhances satellite value and reduces ground operation expenses by shifting intelligence to satellites.
EO Core Systems Providers: Private entities developing EO satellite systems seek business success. Insight4EO improves system value and efficiency.

These segments prioritise mission success within budgets, revenue generation, and operational efficiency. Institutional customers and Commercial EO operators integrate Insight4EO, while EO core systems providers incorporate it into their offerings.

Added Value

Insight4EO’s value proposition is centered on optimising the data handling and processing for Earth Observation missions, improving the timeliness of data delivery, and reducing the overhead on both data transmission and ground processing. This leads to more efficient mission management and potentially lowers operational costs, which could make EO missions more competitive and effective.

On-board Processing (Feature F1):

Up to 90% data reduction in download to the ground.
Reduced time from tasking to data delivery.
Reduced requirements on ground data processing.

Autonomous Re-planning of Tasking (Feature F2):

Reduced time from tasking to data delivery.
Improved mission efficiency thanks to autonomous re-tasking of unattractive images.
Reduced requirement on mission control staff and tasking procedures.

Re-configurable Data Handling (Feature F3):

Improved efficiency of EO missions.
Improved competitiveness of EO systems providers.
Improved competitiveness of EO systems providers.

Easily Integrated Configurations (Feature F4):

Improved efficiency of EO missions and satellite operations.
Up to 90% data reduction in download to the ground.
Reduced time from tasking to data delivery.

Current Status

The Onboard processing up to L1b is at TRL 9, while the rest of capabilities will be TRL 9 by H2 2025 with a planned IOD.

Tree Species

Objectives of the Product

Forestry companies need accurate and up-to-date data, which traditional forest inventory assessment cannot provide. The more detailed information about a forest is available, the more effective plans and decisions can be made, taking into account individual trees in the forest. Therefore, the goal is to develop an EO-based tree species classification methodology, and the related online service platform based on the needs of key customers in their operational environment.

Forest managers and national parks primarily require high-resolution data for accurate planning, their average area size is smaller, so we serve their needs by using high-resolution multispectral Planet data and geometric data from LiDAR data, providing them with products such as high-resolution tree species maps, individual tree-level invasive species maps and tree volume estimation.

At the same time, public actors and decision-makers require data with national coverage, where we provide data based on time-series Sentinel images for transparency, preparation of various reports, continuous monitoring of the area and identification of intervention areas.

Customers and their Needs

We assessed the customers’ needs before designing the service. For the management and operational planning of the forest assets of state and private forest management companies, national park directorates and accurate knowledge of their area of operation is a prerequisite. The need for a solution that examines large areas in a short time, reduces the need for human resources and evaluates the actual condition of the entire area at the same time arose from the forestry sector.

In order to implement either mechanical or chemical treatments against invasive species at the right time, accurate information, species and individual tree identification is required. For national authorities, a tool which serves data that is independent from data providers and gives the possibility to check the differences, monitor changes and control the whole forestry sector is needed. National agencies, decision makers focusing on adaptation to climate change and/or biodiversity require information and monitoring of large areas to plan mitigation activities against the negative effects of climate change (e.g. forest health decrease, spread of invasive species).

Targeted customer/users countries

The service firstly targets the Hungarian forestry sector, but it can be extended to any countries with mixed forests, mainly focusing areas where LiDAR data is available open source.

Product description

EnviMAP Forest is an online GIS supported map service based on high-resolution multispectral Planet data, LiDAR data and Sentinel satellite imagery to support forest management activities. The online platform offers several products, such as individual tree species maps, estimated timber volume and dendrometric parameters, maps of invasive species, monthly forest monitoring and change detection, and several GIS functions to support the daily work of foresters, authorities and agencies focusing on climate change mitigation. The online map platform enables effective dissemination of information and user-friendly interfacing with customers, without special knowledge or infrastructure needed (fat server/thin client model). Clients can check and manage their data for areas of interest, 24/7 from anywhere there is internet access. Especially for public actors and decision makers, leads are generated and dashboards are available to access important information immediately.

Added Value

The innovation resulting from the project ensures accurate knowledge of the operation area, showing species classification maps and estimates timber volume for the entire area. Accordingly, large areas can be examined in a short time with low human resource requirements, evaluating the actual condition of the entire area at the same time. By using our service, unit costs can be reduced to 5-10 EUR/ha comparing to the 28-32 EUR/ha price of field measurements.

Remote-sensing images also allow the simultaneous mapping of the health status of the forest. The service gives exact data about the location of invasive species and their spread is monitored.
Vegetation maps and monitoring are providing information about reality, and unauthorised activities can be identified. The system generates leads to decision makers where there is a difference between the provided data and the calculated and measured data.

With the implementation of continuous monitoring, up-to-date information is available regarding the changes occurring in the forests (vegetation changes, forest growth). If the proportion of the change (spread of invasive species, infections, damages, etc.) is larger than 5% of the given plot, leads/alerts are generated that warn end users and decision makers to analyse the issue.

Current Status

The kick-off of the project was on 31 May 2024. After the kick-off, we started to develop a questionnaire for end users. We will use the results of the questionnaire to finalise key products and functions of the service and to determine the prices of registration and individual map products.

The backbone of the online platform used during InCubed is similar to our earlier development carried out for decision support purposes for agricultural insurance.

Furthermore, we have developed a methodology in the past, for estimating timber volume and have created a workflow with associated methodological documentation that can determine the position and dendrometric characteristics of the timber from LiDAR point cloud. Th second milestone of our project covers the update, adaptation and integration of these modules to an online platform. Our second milestone also includes the development of image classification workflows for species level classification by using Planet and Sentinel EO data combined with tree canopy polygons generated from aerial LiDAR

Combine InSAR

Objectives of the Product

An important task of facility management is regular motion monitoring – checking whether the structure or its parts are moving. In the case of strategic infrastructures – such as roads, railways, bridges or industrial facilities – the motion monitoring is required by law and industry standards.
Currently, these monitoring activities are carried out exclusively using field surveying, which requires personal presence, therefore significant human resources and cost. It is carried out with low temporal frequency – a few times a year – and, as a result, gives relatively few measured points and point density.
By using the project’s solution, the field surveying method could be partially replaced by radar based (InSAR) motion analysis. The application allows the land surveying and InSAR processing data to be managed, analysed and represented together with user-friendly functions.

The ability to import and transform the land survey data from most popular formats.
The hybrid data analysis using InSAR and land survey data together, time gap management and prediction functionalities.
The management functions for the processing area and the facility data.
The possibility of integration to other system, in particular to Building Information Modelling (BIM)-based facility management systems.
Advanced modules for customisable alert system and notification services.

Customers and their Needs

The targeted customer segment of the portal application are the road and railway network operators and maintainers, industrial plant maintainers and land surveying experts, who already perform motion detection of facilities or infrastructures by using field surveying data. Their main task is to prevent the facility’s damages, and their main points are the following:

Personal presence is required.
High-resource demand (human, car, surveying equipment)
Relatively few measured points and point density.
Measuring certain sites is difficult due to physical, operational or legal reasons.

The use of the web portal and its services provides the following advances to customers:

Significantly higher measurement frequency and point density.
Data visualisation and analysis functions.
Less on-site presence and costs.
Motion monitoring results can be shared easily among the surveyor, maintainer and authorities.

The added value lies in the possibility for the user to upload his previous land surveying measurement results in the form of CAD file exchange formats. These data and the results of the SAR based motion analysis are displayed and evaluated together. The end result is a hybrid application in which the results of two very different motion analysis methodologies can be interpreted together.e requirement definition phase, as they can provide information on the environmental and mechanical constraints for a typical EO mission. This information is used to derive board thermo-mechanical constraints, definition of physical interfaces, size and expected power consumption of the module.

Targeted customer/users countries

Hungary, Austria, Benelux Union

Product description

The main components of the product that provide the services of the application are:

Ground motion detection portal (at top of the figure below)
Registration, login/logout and user management services
Upload service for land survey data
Order service for InSAR data processing
Advanced data analysis services
Business logic management services
BIM integration services

The application provides clear and simple user interfaces. The appropriate front-end technology, the integrated map application and the client-side and third-party-based functions (editing data, viewing graphs) together ensure reliable use.
The application and the service components are scalable, the asynchronous functions provide predictable response times. The system ensures multitenant operation.

Added Value

The main focus of the solution is handling and analysing the two very different data sources (InSAR Line of sight, East/West, Vertical measurement versus the land surveying’s classical coordinate system and standards), with a market-oriented approach. Also, if the profession and industry accept, those InSAR results can be successfully used for motion analysis and infrastructure monitoring. Although competitors operate several web portals for displaying InSAR data and advanced data analysis in various fields, the joint use of data sets, data loading, visualisation, joint analysis and weighting, as well as services integrated with BIM systems, can be evaluated as unique. Weighting of the InSAR and land survey data also can be key to penetrate the market, by using different spatial methods like IDW, GWR, trend surface analysis.

Current Status

The kick-off meeting of the project was held on 21 August 2024. The activity is in the onboarding phase, the tasks related to the completion of the first milestone (RR) have begun.
The following technical work is being implemented:

Consultations with partners and potential customers.
Preliminary examination of the sample areas from the point of view of the quality of InSAR results available for the areas.
Negotiation with the supplier regarding to geodetic data available for sample areas

HPCEX

Objectives of the Product

The current needs for Earth Observation (EO) satellites are evolving and we are witnessing an increasing quantity of data to be processed on-board, which is also correlated with the need for complex algorithms running on-board to process all the data in an efficient way, based on Artificial Intelligence and parallel computing. Currently, available solutions are based on commercial components able to address small satellites with very-low availability and reliability requirements. Potentially qualified solutions are being considered, based on AMD Versal with very-high power consumption and dissipation, suitable today only for very big platforms or telecom satellites. Consequently, there is a technology gap for data-processing modules on-board satellites. In particular, for high-reliability (class 1) medium-to-big EO satellites, a qualified solution to address high-performance parallel computing and AI is currently missing. Additionally, a qualified high-performance computing solution is also missing for high-availability/high-reliability smaller platforms, commercial satellites and constellations. The product that is offered to customers at the end of the activity is a high-end edge processing module qualified for class 1 missions. The module is based on a processing board, including a space-qualified GPU, to allow parallel computing acceleration and Artificial Intelligence algorithm implementation.

Customers and their Needs

Target customers for the high-end edge processing module are:

Large System Integrators
- Software companies developing on-the-edge processing applications will be subcontracted by LSI to develop the software on the processing module
Software companies developing on-the-edge processing applications
Hardware provider companies for unit or satellite integration, targeting both big and small satellites
R&D institutions to use it as a proof-of-concept board or in-orbit demonstrator

The target customer is involved during the requirement definition phase, as they can provide information on the environmental and mechanical constraints for a typical EO mission. This information is used to derive board thermo-mechanical constraints, definition of physical interfaces, size and expected power consumption of the module.

Customer Segments	Customer Segment Problems/Needs	Customer Jobs STEP 1	Pain STEP 2	Gain STEP 3
Large System Integrator and unit developer	Reliable and qualified high-performance accelerator for EO	Integrate qualified components/units on satellites	Class 1 missions require class 1 hardware accelerators, which are not available on market	considerable processing power; standardised data interface; reducing total costs and time-to-market.
NSE integrator companies	high-performance data handling and processing accelerator for EO	Providers of Commercial Platforms within New Space Economy	Data Handling and Data Processing boards are very complex to be designed and consumes most of the resources of a satellite developer.	Reducing time-to-market and costs; ease of programming; standardise data interface; enhanced processing power
Software companies	Develop on-the-edge processing applications	Developing custom AI applications for on-the-edge processing hardware	Limited developing flow on custom or reliable board for space system	ease of programming; customisable software flow; dedicated functions; AI enabler;
Software companies	Develop on-the-edge processing applications	Porting of AI of parallel application for on-the-edge processing	Automatic porting tools do not support custom function or layers
R&D institutions	High cost of reliable solution; lack of equivalent boards	Design proof-of-concept board or in-orbit demonstration	Universities and R&D institutions require prototyping hardware that resembles the flight model with limited cost	ease of programming; customisable software flow; dedicated functions; AI enabler; research and development;

Targeted customer/users countries

Europe. The target customers are companies working on the unit or satellite integration, or software companies who need to design the flight software to address the satellite mission requirements.

Product description

The product consists in a space-qualified printed-circuit board, including programmable devices to support high-performance computing, suitable for parallel processing and Artificial Intelligence algorithm implementation. figure below shows the product overall architecture its key modules and major interfaces.

The product is composed by:
A Printed-Circuit Board, which includes the Main FPGA and companion FPGA, memory modules, power modules, standard or custom backplane interface and various standard interfaces commonly used in space applications (SpaceWire, CAN, discrete LVDS, SpaceFibre/WizardLink).
The product is a flexible processing module that will be able to accommodate different kinds of missions by offering:

considerable processing power
ease of programming (presence of a GPU for AI acceleration GPU@SAT)
flexibility in terms of data interfaces (the most common interfaces used for space applications are included)
qualified solution for class 1 mission (thanks to rad-hard components and qualified design)

Low-cost commercial missions can also benefit from such an off-the-shelf solution because a low-cost version of the product will be produced to cover the needs of such missions.
This solution will enable new mission concepts involving even more challenging mission requirements, thanks to the increased processing capabilities in a qualified solution for the space segment.

Added Value

The product delivered to the customer is a space-qualified solution for on-board high-performance computing suitable for parallel processing and Artificial Intelligence processing. The solution is suitable for both high reliability mission and for low-cost commercial missions. As the sensor data volume and algorithm complexity to be run on board the satellite are growing, it is not feasible to satisfy all the requirements with existing solutions. We are providing customers with a qualified solution suitable for high performance computing, ready to be integrated into electronic units or small platform. Building such a system from scratch requires a diverse set of engineering skills together with a large manpower commitment and development time. These required resources are typically not available in a unit or system integrator company. Therefore, the availability of such a product on the market will be very beneficial, saving a huge amount of time and money.

Current Status

The project has just kicked off. A preliminary set of requirements is already defined. Currently, we are engaging customers to provide feedback on environmental, mechanical and interface requirement. With these feedbacks, requirements definitions will be refined.

HPC4AI: NANOhpc – obc

Objectives of the Product

Its development will be focused on a high-performance computer with an integrated AI accelerator, called NANOhpc, addressing the increasing market need in the domain of AI on edge. NANOhpc will enable customers to achieve greater availability for on-board real-time processing of data and transforming it into information, all in an efficient and important, radiation-reliable manner.

For this reason, we propose a high-performance computer with an integrated AI accelerator. The computer will be designed to accommodate a variety of future expansion cards to fit various use case demands. Finally, it will be designed in a highly scalable manner to increase computational capacities as required for each use case. Additionally, it will provide a solution where satellites as-a-service need to be isolated between computational nodes (containers) for security reasons.

The objective of this activity is the development and qualification of the NANOhpc hardware and software framework for a range of mission types. To support this, NANOhpc covers the full range of mission types, from CubeSat lifetimes and integration constraints to larger LEO satellites for 8+ year missions. Processing capacities, and consequently mass, power, and volume requirements, can be tailored by NANOhpc clustering to the mission class and the responsiveness needs of the mission.

Customers and their Needs

NANOhpc, a high-performance computer with built-in AI acceleration, is addressing the space industry’s growing demand for advanced processing power. Several organizations are exploring its potential. Some aim to leverage NANOhpc for on-board Earth Observation, enabling real-time data analysis directly on satellites. Others see advantages in using NANOhpc for in-orbit AI-powered data processing, reducing reliance on ground stations. Additionally, companies are considering validating their on-board processing software with NANOhpc to ensure compatibility and unlock its processing power. Finally, NANOhpc’s design makes it a strong foundation for future high-performance computing with AI on satellites, paving the way for innovative space missions.

Targeted customer/users countries

Italy, Spain, France, Slovenia.

Product description

NANOhpc is a high-performance computer in development for space missions. It offers scalable processing power for nano-satellites to large-satellites. A single unit delivers exceptional performance at low-power consumption and features standard space interfaces. NANOhpc+VB integrates an AI accelerator for complex processing tasks. Notably, the design prioritises radiation tolerance with built-in safeguards and meticulous component selection. Low-power consumption simplifies thermal management and allows for efficient clustering. Overall, NANOhpc’s innovative features make it a compelling solution for the space industry.HPC Architecture.

Added Value

NANOhpc offers a modular and adaptable solution of on-board data processing engines in satellites. Here’s why it brings added value:

NANOhpc system will provide various AI processing engines to provide the best fit for application needs.
NANOhpc system is providing powerful data processing capacity that turns data into information in space, drastically reducing downlink requirements and shortening information delivery to the end user
NANOhpc Scalability: The base version with 4 RISC-V CPUs tackles general processing needs. For demanding missions, the VectorBlox accelerator in NANOhpc+VB tackles complex AI tasks. NANOhpc-FPGA further extends capabilities with custom functions.
NANOhpc Radiation Tolerance: The entire system prioritises radiation tolerance, ensuring reliable operation in space.
NANOhpc Flexibility: This modular approach allows you to choose the processing power and functionalities that best suit your specific mission needs, avoiding overpaying for unnecessary features.

In short, NANOhpc provides a scalable, adaptable, and radiation-tolerant solution for on-board processing in satellites, offering significant value through its tailored approach

Current Status

The NANOhpc project is nearing the end of its definition phase, during which we planned hardware and firmware development activities. In the upcoming PDR meeting, we will finalise requirements and officially transition into the development phase. Over the next few months, we will focus on hardware and software development.