@article{BjelicaITSM2023b,
title = {Human-Centric Role in Self-Driving Vehicles: Can Human Driving Perception Change the Flavor of Safety Features?},
author = {Bojan Mrazovac and Milan Z. Bjelica},
url = {https://ieeexplore.ieee.org/document/9773320},
doi = {10.1109/mits.2022.3169597},
issn = {1939-1390},
year = {2023},
date = {2023-01-01},
journal = {IEEE Intelligent Transportation Systems Magazine},
volume = {15},
number = {1},
pages = {117-125},
publisher = {Institute of Electrical and Electronics Engineers (IEEE)},
abstract = {Autonomous vehicles are expected to generate significant revenues for the global economy in the next decade. Recently, industry experts warned that autonomous vehicles are losing momentum. Self-driving is stalling. Fusing human sentiment and driving perception into a holistic approach to the development of human-centric autonomous vehicles could regain the market’s trust. In this article, we try to explain why the traditional approach to self-driving vehicles, which focuses only on perfecting vehicle performance, sends engineers back to the whiteboard.},
howpublished = {M21},
keywords = {automotive, functional safety, human detection},
pubstate = {published},
tppubtype = {article}
}

@article{letters1,
title = {Device-free indoor human presence detection method based on the information entropy of RSSI variations},
author = {Bojan Mrazovac and Branislav Todorović and Milan Z. Bjelica and Dragan Kukolj},
doi = {10.1049/el.2013.1041},
issn = {0013-5194},
year = {2013},
date = {2013-11-07},
urldate = {2019-01-23},
journal = {Electronics Letters},
volume = {49},
number = {22},
pages = {1386 - 1388},
abstract = {At microwave frequencies, absorption by molecular resonance is a major factor affecting radio propagation. Irregularities in the radio propagation pattern, expressed in a form of the received signal strength indicator's (RSSI) variations, can indicate the possible presence of a human within the radio network. The proposed human presence detection method is based on the information entropy calculated over a set of principal components extracted from a sequence of RSSI samples incrementally, without estimating the covariance matrix. By applying the entropy algorithm, the information on human presence is quantified from the sequence of principal components. It is shown that throughthe- wall human activities, which introduce disturbances in the RSSI footprint of the monitoring room, do not affect the detection accuracy of the method. Experimental results obtained for the 2.4 GHz indoor radio network assess the feasibility of the proposed approach.},
howpublished = {M22},
keywords = {human detection, ieeexplore, RSSI, smart homes},
pubstate = {published},
tppubtype = {article}
}

@conference{Mrazovac2013b,
title = {Reaching the next level of indoor human presence detection: An RF based solution},
author = {Bojan Mrazovac and Branislav Todorović and Milan Z. Bjelica and Dragan Kukolj },
doi = {10.1109/TELSKS.2013.6704936},
isbn = {978-1-4799-0899-8},
year = {2013},
date = {2013-10-16},
booktitle = {Telecommunication in Modern Satellite, Cable and Broadcasting Services (TELSIKS), 2013 11th International Conference on},
publisher = {IEEE},
address = {Nis, Serbia},
abstract = {The presence of a human in the vicinity of radio transceivers results in radio signal strength variations at the receiver's input. Therefore, human presence in an indoor environment can be recognized by analyzing and quantifying irregularities in the radio signature. In order to quantify the information in terms of human presence, we present a novel human presence detection method based on information entropy extracted from a sequence of received signal strength samples. As opposed to existing smart home solutions that incorporate a complex set of sensors for human detection, the proposed method is solely based on radio irregularity phenomenon, without modifying the original environment. An additional level of sensor intelligence is introduced without sensors and installation costs, or specific training procedures for end-consumers.},
howpublished = {M33},
keywords = {human detection, ieeexplore, RSSI, user monitoring},
pubstate = {published},
tppubtype = {conference}
}

@article{comsis1,
title = {System Design for Passive Human Detection using Principal Components of the Signal Strength Space},
author = {Bojan Mrazovac and Milan Z. Bjelica and Dragan Kukolj and Branislav Todorović and Saša Vukosavljev},
doi = {10.2298/CSIS120531010M},
issn = {1820-0214},
year = {2013},
date = {2013-01-01},
journal = {Computer Science and Information Systems},
volume = {10},
number = {1},
pages = {423-452},
abstract = {In this article, device-free human presence detection method based on principal components analysis of the radio signal strength variations is proposed. The method increases user awareness for automated power management interaction in residential power saving systems. Motivation comes from a need for decreasing the installation complexity and development costs induced by the integration of specific human presence detection sensors. The method exploits the fact that a human body interferes with radio signals by introducing irregularities in the radio signature which indicate possible human presence. By analyzing radio signals between radio transceivers embedded in 2.4 GHz wireless power outlets, the original environment is not visually modified and a certain level of sensorial intelligence is introduced without additional sensors. The analysis of the signal strength variations in principal components space enhances the detection accuracy level of human presence detection method, retaining low installation costs and improving overall energy conservation.},
howpublished = {M23},
keywords = {human detection, RSSI, smart homes},
pubstate = {published},
tppubtype = {article}
}

@article{tcem1,
title = {A Human Detection Method for Residential Smart Energy Systems Based on Zigbee RSSI Changes},
author = {Bojan Mrazovac and Milan Z. Bjelica and Dragan Kukolj and Branislav Todorović and Dragan Samardžija},
doi = {10.1109/TCE.2012.6311323},
issn = {0098-3063},
year = {2012},
date = {2012-09-27},
journal = {IEEE Transactions on Consumer Electronics},
volume = {58},
number = {3},
pages = {819-824},
abstract = {In this article, the device-free human presence detection method based on radio signal strength variations is proposed. The method exploits the known fact that human body interferes with radio signals by causing fading and shadowing effects. Introduced irregularities in the radio propagation pattern indicate possible presence of a human. The proposed method is incorporated into the existing platform for intelligent residential energy management. As opposed to conventional solutions which utilize a complex set of sensors for human detection, the proposed approach achieves the same only by analyzing and quantifying radio signal strength variations incorporated in messages exchanged between 2.4 GHz radio transceivers. One of the key benefits of the proposed solution is the integration of the detection algorithm into the smart power outlets and smart light switches. Such an approach improves interactions in smart home systems, enables intelligent power consumption management and low installation cost.},
howpublished = {M22},
keywords = {human detection, ieeexplore, RSSI, smart homes, user monitoring, zigbee},
pubstate = {published},
tppubtype = {article}
}