Expertises

Based on historical data, future usage and developments can be predicted using machine learning algorithms. Typical behavioral patterns and influencing factors are identified, from which a precise forecast can be made for the coming hours, days and years. These predictions are available via API or directly in our user-friendly Diamond Reports web tool.

New insights often arise when different data sources are brought together. We harmonize your data sources from different formats, evaluate the data and merge them. This allows you to carry out advanced analyses and discover previously unnoticed dependencies. The processed data can be integrated into the Diamond Reports web tool or fed into databases via API interfaces.

ASE maintains close ties with leading global research universities and fosters a regular exchange of knowledge with academics worldwide. Some of our employees also teach, for example, at ETH Zurich. This makes the university not only an important recruitment channel for new talent for the company. ASE's technologies and datasets have been used in a variety of scientific studies, which have been published. ASE also conducts its own research, the results of which are presented in scientific journals, at symposiums, or industry conferences.

Jessica Weibel, MSc. ETH Spatial Development and Infrastructure Systems, was a project manager at ASE. She received the VSS Award 2020 for her master's thesis on short-term prediction of platform overloads using supervised machine learning. VSS article available in Strasse und Verkehr issue 03/2020 at www.vss.ch.

Application of new sensors for pedestrian detection for assessing safety risks on platforms at Swiss and Dutch train stations (van den Heuvel et al., 2019)

A published scientific paper that uses ASE's technology and proprietary stitching algorithm to achieve a high degree of accuracy "even at the highest levels of complexity", as defined in the study.

Destination Choice Modeling with Spatially Distributed Boundary Conditions (Vitins & Erath, 2019)

A contribution by Basil Vitins, Head of Modeling and Simulations at ASE, presented at the Swiss Transport Conference 2019 in Ascona. The choice of travel destination is an important factor for economic processes and social structures.

ASE supplies measuring systems for the Federal Ministry's CroMa project

The CROMA project is an initiative funded by the German Federal Ministry of Education and Research (BMBF) that aims to improve the robustness, safety and performance of transport hubs for the approximately 36 million passengers who use German public transport every day in September 2020 through improved building regulations, appropriate crowd management and cross-organizational implementation guidelines. The project is being led by leading research authority Prof. Dr. Armin Seyfried, who is relying on the ASE technology used at Frankfurt Central Station and the data collected: www.croma-projekt.de

Risk Based Maintenance (RBM) – Minimizing user risks and operating costs with a risk-based method for BSA maintenance

In road tunnels, operational and safety equipment (OSE) is installed, the failure of which poses risks to traffic, operators, and the environment. Regular maintenance reduces these risks but incurs costs. This study describes a risk-based maintenance methodology that makes maintenance strategies comparable in terms of costs and risks. This allows for the determination of the optimal strategy for individual facilities or an entire portfolio to minimize risk given a certain budget, or vice versa.
https://myvss.mobilityplatform.ch//vss/account/publication/2818/webviewer/

E-Scooters: Traffic Planning Implications and Future Requirements

E-scooters are increasingly important in Switzerland, already utilizing existing traffic areas alongside cars, public transport, pedestrians, cyclists, and e-bikes. Their growing presence in public spaces leads to conflicts, such as improper parking or prohibited use on sidewalks, and raises questions about sustainability. This paper examines the traffic planning implications of e-scooters and derives requirements for infrastructure and network planning.
https://myvss.mobilityplatform.ch//vss/account/publication/8081/webviewer/

Methods of Traffic Survey Standard VSS 40 003
 

The report lays the foundation for the standard VSS 40 003: Surveys and is based on a literature analysis as well as a practical survey in Switzerland. It shows that methods, data sources, and thematic priorities of traffic surveys have been greatly expanded by digitalization, new forms of mobility, and higher data granularity. The findings gained form the basis for adapting the standard to the current needs of practice.
https://myvss.mobilityplatform.ch//vss/account/publication/8076/webviewer/

Custom AI Pipelines for Productive Applications

We develop custom AI pipelines that are specifically tailored to our clients' requirements – from data acquisition and model training to stable operation in edge and cloud environments. We combine software engineering, data science, and MLOps to create an end-to-end, scalable solution.

Our AI pipelines are designed for reliable real-world operation. They integrate seamlessly into existing system landscapes, support real-time processing, and enable controlled rollouts of new models. This results in AI solutions that are not only technically convincing but also create long-term economic added value.

Integration as the basis for continuous digital solutions
We don't see integration as a technical side task, but rather as a central building block for stable and scalable digital solutions. Our integration architectures connect edge, IoT, and cloud components with existing IT systems, creating seamless, reliable data flows – from data acquisition to utilization in operational and analytical applications.

Modern Interfaces and Event-Driven Architectures
We rely on proven standards and scalable technologies to flexibly connect different systems. This includes classic REST APIs, event-based interfaces such as MQTT, as well as webhooks for event-driven integrations.
For complex and highly scalable data streams, we use Kafka to decouple systems, enable real-time processing, and reliably handle large amounts of data. This creates integrations that are not only functional but also future-proof and expandable.

Secure, scalable, and reliable
Security is an integral part of our integration solutions. Data is transmitted encrypted, access is clearly authenticated and controlled based on roles. Our interfaces are designed for continuous operation, high load, and growing system landscapes – even in distributed and business-critical environments.

Experience from real-world IT landscapes
We have extensive experience with heterogeneous and legacy system landscapes. Instead of isolated point-to-point connections, we create clearly defined interfaces, clean data models, and structured further development. The result is integrations that are maintainable, understandable, and sustainable in the long term.

Self-Service Analytics, Enabling Decisions

We develop customized self-service analytics solutions that translate complex data into clear, understandable metrics. The focus is on users who need to make daily decisions – not on technical specialists.

Our solutions combine real-time and historical data in a unified interface, offering pre-defined KPIs, dashboards, and comparison logic. Users receive exactly the information they need – without technical dependencies, but with clear structure and guidance. This creates self-service analytics that empower action, rather than overwhelming users.

The solutions can be seamlessly integrated into existing systems or embedded directly into customer-owned applications. They are scalable across locations and organizations, forming a reliable foundation for operational and strategic decisions.

Reliable operation requires more than good technology – it needs clear processes, transparency, and fast response times. We offer professional incident management that maps and scales all service processes seamlessly.
Seamless processes without loss of information
Support, development, and operations are integrated into a unified system. All information is consistently passed along from the initial customer contact through technical processing to the resolution – without media breaks or manual handoffs.
Transparency at all levels
Customers can always see the status of their requests and incidents. Internally, structured workflows enable clear prioritization, assignment, and tracking of all tickets – from critical system failures to configuration adjustments.
Defined service levels
Service level agreements are stored directly in the system and automatically monitored. Response and resolution times are bindingly defined and measurable – for every severity level and every contract type. Escalation processes are automatically triggered before SLA limits are exceeded.
Continuous improvement
The close integration of service management and software development makes it possible to transfer recurring incidents directly into the development process. Identified patterns are systematically analyzed and incorporated into the platform as improvements.

A highly available system requires continuous monitoring at all levels – from field sensors to the central data platform. ASE offers end-to-end monitoring that detects problems before they affect operations.
Sensor & Hardware Monitoring
All connected sensors and field devices are monitored seamlessly. Connection status, signal quality, power supply, and device status are captured and evaluated in real-time. Deviations from normal operation – such as signal loss, measurement errors, or hardware defects – are automatically detected and reported. This allows for targeted and early planning of preventive maintenance measures.
Platform and Software Monitoring
At the platform level, system resources, data throughput, processing times, and interface availability are continuously monitored. Automated test routines validate data quality and detect anomalies in the measurement data before they flow into downstream analyses or applications.
Alerting & Escalation
Thresholds and alarm rules are freely configurable. When thresholds are exceeded, responsible teams are automatically notified – according to defined escalation levels and communication channels. Close integration with incident management ensures that detected problems are immediately recorded and processed as tickets.
Monitoring Dashboard
All relevant system metrics are consolidated in a central dashboard. Operators and service teams receive a uniform, up-to-date overview of the system's overall condition – across locations and in real-time.

A wide variety of sensor types are used to detect the movement of people and vehicles. Each measuring point has different requirements for the sensor, such as incidence of light, degree of soiling and position. ASE uses sensors from third-party suppliers so that we can keep up to date with the latest technological developments on the hardware side and thus use data of consistently high quality for our systems.

Powerful AI right at the point of use
We rely on NVIDIA-based edge computing solutions to reliably and performantly run AI applications directly at the source of data generation. Processing at the edge enables real-time requirements to be met, latencies to be minimized, and data volumes to be significantly reduced.

Experience from productive operation
Our strength lies not only in development but, above all, in the stable operation of edge devices in the field. We have extensive experience with NVIDIA hardware in real-world environments – from commissioning and monitoring to ongoing operation in 24/7 scenarios.

Suitable hardware for every use case
Based on our customers' specific requirements, we recommend the most suitable NVIDIA Edge hardware – from compact Jetson systems to powerful industrial platforms. We consider factors such as computing load, scalability, environmental influences, and operating costs to ensure a future-proof and cost-effective solution.

Reliable networking of devices and systems
Our IoT technology connects sensors, cameras, and devices to an end-to-end, scalable data foundation. We enable the structured capture and transmission of measurement and event data – reliably, manufacturer-independent, and designed for productive use.

Experience in operating distributed IoT systems
We have extensive experience in operating large IoT installations with thousands of devices. This includes device management, monitoring, update strategies, as well as secure and stable operation, even in distributed and demanding environments.

Security and encrypted data transmission
All data is encrypted and transmitted securely, from the source to further processing. Authentication, access control, and proven security mechanisms are an integral part of our IoT architectures. This is how we ensure that sensitive operational and analytical data is protected at all times – even in critical infrastructures.

Intelligent Video Analytics for Real-World Environments
Our video analysis technology transforms video streams from existing cameras into valuable, structured data – in real-time and in compliance with data protection regulations. Instead of storing video material or analyzing it manually, we deliver precise key figures on visitor frequency, utilization, movement patterns, and dwell times.

Real-time processing directly at the edge – GDPR compliant by design
The analysis is performed in real-time directly at the edge, close to the camera. This way, no image or video material is stored or transmitted to the cloud.
Only anonymized metadata is generated – a central building block for GDPR-compliant solutions, especially in public spaces, retail, and public transport.

Proven standard models and customized AI
We rely on robust, field-tested AI models that have proven themselves in numerous production environments. These standard models reliably cover typical use cases such as people and object counting.
For specific requirements, we go a step further:
Together with our customers, we develop and train customized AI models, precisely tailored to the respective use case, environment, and hardware. We draw on our AI pipeline expertise – from data collection and training to stable operation.

Seamless integration into analytics and existing systems
The results of the video analysis are available as structured, immediately usable data and can be flexibly integrated into existing system landscapes. Via standard interfaces such as MQTT, the data can be transferred directly to our reporting frontend, to customer-owned backends, or to further analysis and control systems.
Alternatively, the results can be visualized directly within the application. This transforms video analysis into a continuous database that supports operational processes and enables informed strategic decisions.

Areas of application
Our video analysis is used wherever high visitor numbers, complex movement patterns, and reliable real-time data are required:

• Retail & Shopping Centers
• Stations, airports, and public transport
• Destinations and public spaces

Reporting reimagined. Future-proof, intuitive.

With our solution, data becomes clear, understandable insights: Individually customizable Dashboards show Real-time trends at a glance and deliver well-founded analyses for better decisions.

The platform offers the highest security thanks to ISO 27001-certified infrastructure and GDPR-Compliance. Single Sign-On enables seamless access, and the mobile-optimized interface makes reporting and monitoring available anytime, anywhere. Additional features such as operating hours maintenance and sensor monitoring support you in centrally and efficiently managing all relevant information.

The IBM Maximo Application Suite (MAS) is a modern, integrated software platform for Enterprise Asset Management (EAM). It helps companies efficiently manage, monitor, and continuously optimize their physical assets, machinery, infrastructure, and buildings throughout their entire lifecycle.

MAS combines classic maintenance management with modern technologies such as Artificial Intelligence (AI), IoT data, analytics, and mobile solutions, thereby enabling the shift from reactive maintenance to predictive, data-driven asset management.

MAS is not a single application, but a modular suite of coordinated solutions based on a common technological platform. All modules access the same data, processes, and user interfaces, thus providing a consistent view of assets, maintenance processes, and operating states.

With MAS, companies get a central platform for, among other things:

• To operate systems reliably
• To efficiently manage maintenance processes
•  Detecting failures early
• To reduce costs and risks
• Make informed decisions based on real-time and historical data