The challenging environment, most often below the ground, needs a robust and reliable device with superior radio performance.
The ADM platform includes
- AI based problem detection
- comprehensive device management
- automated device monitoring.
The new AI-based observations are under continuous development, and our customers ideas are included into our innovation process.
Aistio IoT devices are
- designed in Finland for wireless and accurate measurement
- for monitoring industrial processes
- for controlling smart energy solutions
- for monitoring conditions of various buildings
- designed to optimize radio reception.
Continuous Aistio IoT device testing and development have resulted in
- extremely low power consumption
- high reliability
- adhering to strict quality standards
- the use of high-quality components
- developing the product from scratch to mass production through our own efforts.
Aistio IoT devices are RoHS compliant as well as LoRaWAN and CE certified.
Cloud is where the ADM intelligence is
The Aistio District Monitoring web service
- is a SaaS service, multi‑tenant cloud‑based‑software
- can be scaled globally
- supports the highest possible performance whenever needed
- contains world-class security methods
- supports high-standard backup
- has prioritized uptime and availability.
Thanks to basically limitless performance capabilities in the cloud, we can run even the most intelligent and sophisticated AI algorithms in the ADM service.
Security and quality are widely considered from various perspectives in the ADM service.
Various customers have been audited ADM service security to ensure the quality of the security.
Customer driven security audits that have been made:
- OWASP ASVS 3.0 Level 1 – ADM web application met the requirements
- VTT – IoT supplier and solution evaluation checklists – ENISA based security recommendations were met at a commendable level.
We work in close cooperation with various parties involved in cybersecurity, such as The Finnish Transport and Communications Agency Traficom.
As a result, we receive near-real-time information about potential security threats, warnings and vulnerabilities.
Monitoring potential security threats and developing data security is one of the cornerstones of our business.
The ADM service fully complies with the requirements of the General Data Protection Regulation (GDPR) and is according to Soficta’s company-level Data Protection policy, which is reviewed annually.
IoT devices and cloud services collect real data. However, the real benefits of the data are only obtained when the collected data is processed and analysed in the right way and in the right system.
For information management, different systems need to communicate with each other.
Real-time data collected from the network is the basis of
- Artificial Intelligence
- Digital Twins.
ADM Integration API
- is a programming interface
- supports alerts generated by ADM
- provides measurement data collected by ADM
- securely sends alerts and measurement data to third party systems.
For example, the ADM network data can be integrated directly into a production plant optimization system, for instance to the Valmet integration system. This provides an opportunity to find more savings in optimization.
Aistio IoT devices collect large amounts of data due to the nature of measurement data and the large number of connected measurement points.
- can observe various kind of problems and events from the collected data
- can automatize and prioritize important tasks based on observed problems
- is developed in cooperation together with Finnish universities
- uses algorithms to learn step by step from data
- uses algorithms to learn from data and thus develops the model of machine learning.
Aistio AI benefits for customers
- less error proneness
- increased productivity
- improved quality
- employees can focus on value-creating work
- early birds gain a competitive edge
- costs will decrease in the long run.
Big Data and analytics
Our district-heating-specific Big Data will continue to grow larger as AI becomes a more viable option for automating tasks, and as AI becomes a larger field as more data is available for data analysis.
Our target is to have ADM predict what is going to happen, and even better, instruct machine learning algorithms to do specific actions based on these.