Research Infrastructures    Data, Computing & Digital Research
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Internet of Living Things

Description of the RI

The Internet of Living Things (IoLT) research infrastructure enables the development of Internet of Things (IoT) applications by providing easy-to-use programming interfaces for ultra-low-resource devices. Its open source software allows even non-IT researchers to develop biological and medical IoT applications. Related research and development areas of the RI are JavaScript engine, software quality assurance and source code quality, IoT-Cloud infrastructure and simulators; algorithms for ensuring data safety and security.

Activities and Services

In the frame of the national GINOP IoLT project, a novel network of excellence integrating basic research in the IoT field with biological and medical applied research was created. The project, with University of Szeged, a prominent research university with outstanding achievements at the helm of the consortium, was successfully completed in 2021. The Biological Research Centre (BRC) acted as the collaborating consortium member in this project. During the development of the IoLT project, BRC created the IoLT research infrastructure to enable and foster international research in this joint field. With the collaboration of international industrial partners, BRC developed an open source IoLT software platform that allows even non-IT researchers to develop biological, medical, and also conventional IoT applications. The platform enables researchers of any discipline to develop and execute IoT applications by providing easy-to-use programming interfaces and tool sets. The platform supports a wide range of devices in general and ultra-low-resource, ultra-cheap IoT devices in particular. Available components and tools are JavaScript interpreter developed for heavily constrained IoT devices (JerryScript); IoT development environment for rapid application development; tools for software quality assurance including static code analysis, source code quality and vulnerability checks using AI models; device drivers, communications, IoT cloud infrastructure and simulators; algorithms for ensuring data safety and security. Development of the platform is continuous, which includes the adaptation of the core JerryScript execution environment to application-specific peripherals. The development of IoLT applications is facilitated through the high-level programming of ultra-low-resource sensors for adaptive data collection and processing. Simulation tools are developed for investigating the efficient and secure management of IoT applications in fog and cloud systems. Advanced AI tools are available, e.g. for medical applications and natural language processing.

The platform enables the assessment of the impact of environmental factors determining the growth and stress reactions on individual plants. In medical practice the platform supports actigraphic research for identifying new ultradian and slower periodic and stochastic components in human physical activity patterns and establishing their correlation to physical conditions, activities, and certain psychiatric disorders. Devices running the platform can greatly increase the effectiveness of work on cell cultures by facilitating the testing of potential active substances. To increase the efficiency of personalised therapies, the platform can aid the analysis of microscopic images and automatic classification using machine learning methods.

Data, Computing and Digital Research


University of Szeged Institute of Informatics


Fully operational, 2017–


  • ELKH - Biological Research Centre (BRC)


Institutional partners
  • Liverpool John Moores University
  • Samsung Electronics UK Ltd.
  • ARM Ltd.

Prof. Tibor Gyimóthy


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