ARTSS method

ARTSS method

In order to design and deliver secure and resilient services, the ARTSS method has been developed as an extension of the Capability Driven Development. The method provides a structured approach to identification and representation of security and resilience concerns as capability models. The capability models show capabilities and services supporting their delivery as well as capability goals, delivery context and adjustment used to adapt capability delivery in the case of unexpected events such as caused by crisis situations.


IoT Data Analytics in Retail: Framework and Implementation

IoT data analytics has many potential applications in the retail industry. However, relations among ambient conditions at stores as measured by IoT devices and sales performance are not well understood. The study explores sensory and sales data provided by a large retail chain to quantify the impact of air quality, temperature, humidity, and lighting on customer behavior.


On 16 October 2020, the IEEE Information Technology and Management Science Section of the RTU's 61st scientific conference took place.

As part of it, a special session was held on the ARTSS project. Special session time 14.25-14.50.


On October 6, the book journal "Dati kā tehnoloģiju laikmeta resursi: izmantošana un aizsardzība (Data as the Resources of the Technology Age: Use and Protection) came out in the “Jurista Vārds” edition, which also includes the article by ARTSS researchers Rūta Pirta-Dreimane and Jānis Grabis, entitled "Informācijas drošība digitalizācijas laikmetā: izaicinājumi un risinājumi" (“Information Security in the Digital Age: Challenges and Solutions”), which


On 17 September 2020, a scientific seminar was held by the ARTSS consortium, presenting the current scientific results of the project:

  • I. Stefanišina, Model: Effective teleconferencing for a remote working group
  • A. Kapenieks, Innovative Learning Solutions

On 1 September 2020, in the Radio Broadcasting “Zināmais nezināmajā”, Jānis Grabis presented the solutions developed by RTU to identify cyber security threats on large computer network.

The complexity of malicious attacks on large computer networks is increasing, which makes it difficult to timely respond.