Petra Zorić
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Petra Zorić has a total of 37 co-authors. Here are the top co-authors by number of shared publications:
- Dragan Peraković
University of Zagreb
16 shared publications - Marko Periša
University of Zagreb
14 shared publications - Ivan Cvitić
University of Zagreb
13 shared publications Tibor Mijo Kuljanić
Hrvatska Elektroprivreda d.d
5 shared publicationsMario Musa
Hrvatska Lutrija D.O.O.
4 shared publications- Ivan Grgurević
University of Zagreb
3 shared publications
Latest Publications
- Open Access
Empowering People with Disabilities in Smart Homes Using Predictive Informing
The possibilities of the Ambient Assisted Living (AAL)/Enhanced Living Environments (ELE) concept in the environment of a smart home were investigated to improve accessibility and improve the quality of life of a person with disabilities. This paper focuses on the concept of predictive information for a person with disabilities in a smart home environment concept where artificial intelligence (AI) and machine learning (ML) systems use data on the user’s preferences, habits, and possible incident situations. A conceptual mathematical model is proposed, the purpose of which is to provide predictive user information from defined data sets. This paper defines the taxonomy of communication technologies, devices, and sensors in the environment of the user’s smart home and shows the interaction of all elements in the environment of the smart home. Through the integration of assistive technologies, it is possible to adapt the home to users with diverse types of disabilities and needs. The smart home environment with diverse types of sensors whose data are part of sets defined by a mathematical model is also evaluated. The significance of establishing data sets as a foundation for future research, the development of ML models, and the utilization of AI is highlighted in this paper.
Open AccessEmpowering People with Disabilities in Smart Homes Using Predictive Informing
The possibilities of the Ambient Assisted Living (AAL)/Enhanced Living Environments (ELE) concept in the environment of a smart home were investigated to improve accessibility and improve the quality of life of a person with disabilities. This paper focuses on the concept of predictive information for a person with disabilities in a smart home environment concept where artificial intelligence (AI) and machine learning (ML) systems use data on the user’s preferences, habits, and possible incident situations. A conceptual mathematical model is proposed, the purpose of which is to provide predictive user information from defined data sets. This paper defines the taxonomy of communication technologies, devices, and sensors in the environment of the user’s smart home and shows the interaction of all elements in the environment of the smart home. Through the integration of assistive technologies, it is possible to adapt the home to users with diverse types of disabilities and needs. The smart home environment with diverse types of sensors whose data are part of sets defined by a mathematical model is also evaluated. The significance of establishing data sets as a foundation for future research, the development of ML models, and the utilization of AI is highlighted in this paper.
- Open Access
- 15 November 2024
- Published by MDPI AG in Preprints.org
Empowering Person with Disabilities in Smart Home Using Predictive Informing
The possibilities of the Ambient Assisted Living (AAL)/Enhanced Living Environments (ELE) concept in the environment of a smart home were investigated to improve accessibility and improve the quality of life of person with disabilities. This paper focuses on the concept of predictive information for person with disabilities in a smart home environment concept where artificial intelligence (AI) and machine learning (ML) systems use data on the user's preferences, habits, and possible incident situations. A conceptual mathematical model is proposed, which purpose is to provide predictive user information from defined data sets. The paper defines the taxonomy of communication technologies, devices, and sensors in the environment of the user's smart home and shows the interaction of all elements in the environment of the smart home. Through the integration of assistive technologies, it is possible to adapt the home to users with different types of disabilities and needs. The smart home environment with diverse types of sensors whose data are part of sets defined by a mathematical model is also evaluated. The significance of establishing data sets as a foundation for future research, development of ML models, and utilization of AI is highlighted in this paper.
- 15 November 2024
- Published by MDPI AG in Preprints.org
Open AccessEmpowering Person with Disabilities in Smart Home Using Predictive Informing
The possibilities of the Ambient Assisted Living (AAL)/Enhanced Living Environments (ELE) concept in the environment of a smart home were investigated to improve accessibility and improve the quality of life of person with disabilities. This paper focuses on the concept of predictive information for person with disabilities in a smart home environment concept where artificial intelligence (AI) and machine learning (ML) systems use data on the user's preferences, habits, and possible incident situations. A conceptual mathematical model is proposed, which purpose is to provide predictive user information from defined data sets. The paper defines the taxonomy of communication technologies, devices, and sensors in the environment of the user's smart home and shows the interaction of all elements in the environment of the smart home. Through the integration of assistive technologies, it is possible to adapt the home to users with different types of disabilities and needs. The smart home environment with diverse types of sensors whose data are part of sets defined by a mathematical model is also evaluated. The significance of establishing data sets as a foundation for future research, development of ML models, and utilization of AI is highlighted in this paper.
- 14 March 2023
- Published by Springer Nature
- p. 211-225
Opportunities of Using Machine Learning Methods in Telecommunications and Industry 4.0 – A Survey
- 14 March 2023
- Published by Springer Nature
- p. 211-225
Opportunities of Using Machine Learning Methods in Telecommunications and Industry 4.0 – A Survey
- 14 March 2023
- Published by Springer Nature
- p. 3-14
Concept, Architecture, and Performance Testing of a Smart Home Environment for the Visually Impaired Persons
- 14 March 2023
- Published by Springer Nature
- p. 3-14
Concept, Architecture, and Performance Testing of a Smart Home Environment for the Visually Impaired Persons
- 18 September 2022
- Published by Springer Nature
- p. 141-152
Information Service for the Visually Impaired Persons in Public Transport – MAppIN
- 18 September 2022
- Published by Springer Nature
- p. 141-152
Information Service for the Visually Impaired Persons in Public Transport – MAppIN
- 17 June 2022
- Published by Springer Nature
- p. 115-128
Modeling the Purchase Process of the InnIoTShop Solution in a Store Environment
- 17 June 2022
- Published by Springer Nature
- p. 115-128
Modeling the Purchase Process of the InnIoTShop Solution in a Store Environment
- 1 January 2022
- Published by Springer Nature
- p. 129-142
Use of Probabilistic Risk Assessment Methodology for Providers of Services in a Virtual Environment
- 1 January 2022
- Published by Springer Nature
- p. 129-142
Use of Probabilistic Risk Assessment Methodology for Providers of Services in a Virtual Environment
- 1 January 2022
- Published by Springer Nature
- p. 143-158
Challenges of Improving the Railway Passenger Information System in the Republic of Croatia
- 1 January 2022
- Published by Springer Nature
- p. 143-158
Challenges of Improving the Railway Passenger Information System in the Republic of Croatia
- 3 August 2021
- Published by Springer Nature
- p. 379-395
Use Case: Information Security Risk Assessment for Providers of Services in a Virtual Environment
- 3 August 2021
- Published by Springer Nature
- p. 379-395
Use Case: Information Security Risk Assessment for Providers of Services in a Virtual Environment