TY - GEN A1 - Löffler, Sven A1 - Becker, Ilja A1 - Bückert, Carlo A1 - Hofstedt, Petra ED - Gini, Giuseppina ED - Nijmeijer, Henk ED - Filev, Dimitar T1 - Enhanced Optimal Beacon Placement for Indoor Positioning: A Set Variable Based Constraint Programming Approach T2 - Proceedings of the 20th International Conference on Informatics in Control, Automation and Robotics : November 13-15, 2023, in Rome, Italy, volume 1 KW - Beacon Placement KW - Constraint Programming KW - Decision Support Systems KW - Artificial Intelligence Y1 - 2023 SN - 978-989-758-670-5 U6 - https://doi.org/10.5220/0012203400003543 SP - 70 EP - 79 PB - Scitepress ER - TY - GEN A1 - Löffler, Sven A1 - Abbenhaus, Viktoria A1 - Assaf, George A1 - Hofstedt, Petra ED - Gini, Giuseppina ED - Precup, Radu-Emil ED - Filev, Dimitar P. T1 - Solving the three-dimensional beacon placement problem using constraint-based methods, large neighborhood search, and evolutionary algorithms T2 - Proceedings of the 22nd International Conference on Informatics in Control, Automation and Robotics : Volume 1 : ICINCO N2 - With the increasing prevalence of large building complexes, indoor localization is becoming an area of growing significance. In critical situations, such as emergencies in factories or care facilities, the ability to locate a person quickly can be a matter of life and death. One possibility for localization are Bluetooth beacons, which are either attached to the person or in rooms. We pursue the latter approach, whereby the beacon signals are used to determine the position of a receiving device, e.g. a mobile phone. At this, the use of a sufficient number of beacons in the building must be ensured in order to guarantee adequate coverage. However, to minimize costs, it is equally important to avoid placing unnecessary beacons. This creates a challenging optimization problem that this paper addresses through three distinct approaches: constraint programming, large neighborhood search, and evolutionary algorithms. Using simulated three-dimensional buildings, we test and evaluate these m ethods, ultimately providing a practical and efficient approach applicable to real-world building environments. KW - Constraint Programming KW - AI Algorithms KW - Beacon Placement Y1 - 2025 SN - 978-989-758-770-2 U6 - https://doi.org/10.5220/0013724500003982 SP - 105 EP - 116 PB - SciTePress - Science and Technology Publications CY - Setúbal, Portugal ER - TY - CHAP A1 - Löffler, Sven A1 - Hofstedt, Petra ED - Gini, Giuseppina ED - Nijmeijer, Henk ED - Filev, Dimitar T1 - Enhanced optimal beacon placement for indoor positioning : refining the search process T2 - Informatics in control, automation and robotics : 20th International Conference, ICINCO 2023, Rome, Italy, November 13–15, 2023 : revised selected papers N2 - Indoor localization plays a key role across diverse environments such as hospitals, retirement homes, and emergency response scenarios. Ensuring the efficient and precise tracking of mobile individuals indoors heavily relies on the strategic deployment of sensors. Manual placement of beacons (sensors) for indoor positioning within a building poses significant challenges and time constraints. Consequently, numerous researchers have explored this problem domain, employing diverse algorithms and addressing various practical scenarios. In our previous works at the ACS/IEEE International Conference on Computer Systems and Applications (AICCSA 2022) [20] and the 20th International Conference on Informatics in Control, Automation and Robotics (ICINCO 2023) [19], we introduced two novel approaches that leverage constraint programming with exclusively Boolean variables respectively only set variables and Boolean variables to efficiently place Bluetooth Low Energy (BLE) beacons in indoor scenarios. We evaluated the quality of our results by comparing them against manually optimized beacon placement and assessing their performance in four real-world school buildings. This paper extends the findings of [19, 20] by new approaches on the search in the constraint solving process using greedy search and local search techniques. KW - Constraint Programming KW - Search Methods KW - Beacon Placement Y1 - 2025 SN - 978-3-031-94989-0 U6 - https://doi.org/10.1007/978-3-031-94989-0_5 SN - 1876-1100 SP - 97 EP - 124 PB - Springer Nature Switzerland CY - Cham ER -