| 1. |
- Azizi, Shoaib, et al.
(författare)
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Application of Internet of Things in academic buildings for space use efficiency using occupancy and booking data
- 2020
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Ingår i: Building and Environment. - : Elsevier. - 0360-1323 .- 1873-684X. ; 186
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Tidskriftsartikel (refereegranskat)abstract
- Environmental sustainability in academic buildings can be improved with management interventions such as improving space use efficiency supported by large data from the Internet of Things (IoT). Due to the potentials, the interest in the use of IoT tools for facility management is high among universities. However, empirical studies on this topic are scarce. To address the knowledge gap in this area, this study proposes and examines a process model with steps to measure space use and to improve space use efficiency by IoT tools in academic buildings. The applicability of the model is investigated in 8 lecture halls in a university building by using occupancy and booking data from IoT tools. Four space use indicators are developed to visualize the data and quantify space use, and based on them, the strategies and interventions for space use efficiency are proposed and discussed.
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| 2. |
- Azizi, Shoaib, et al.
(författare)
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Application of occupancy and booking information to optimize space and energy use in higher education institutions
- 2020
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Ingår i: E3S Web of Conferences. - : EDP Sciences. - 2267-1242. ; 172
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Tidskriftsartikel (refereegranskat)abstract
- Building in higher education institutions (HEIs) are characterized as energy intensive Experience from practice showing large discrepancies between predicted and actual energy performance. The deviation can sometimes reach 100%. Explanations often originate from occupant’s behaviour along with building operation. IoT-based smart tools can provide extensive information about building usage to improve the building management, often associates with opportunities, for significant energy saving. The analysis in this study investigate space use based on occupancy and booking information in eight different lecture rooms at Umeå University. The results suggest interventions for significant saving potentials, such as modification of access permission and closing down redundant lecture rooms.
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| 3. |
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| 4. |
- Azizi, Shoaib, et al.
(författare)
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Effects of Positioning of Multi-Sensor Devices on Occupancy and Indoor Environmental Monitoring in Single-Occupant Offices
- 2021
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Ingår i: Energies. - : MDPI. - 1996-1073. ; 14:19
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Tidskriftsartikel (refereegranskat)abstract
- The advancements in sensor and communication technologies drive the rapid developments in the applications of occupancy and indoor environmental monitoring in buildings. Currently, the installation standards for sensors are scarce and the recommendations for sensor positionings are very general. However, inadequate sensor positioning might diminish the reliability of sensor data, which could have serious impacts on the intended applications such as the performance of demand-controlled HVAC systems and their energy use. Thus, there is a need to understand how sensor positioning may affect the sensor data, specifically when using multi-sensor devices in which several sensors are being bundled together. This study is based on the data collected from 18 multi-sensor devices installed in three single-occupant offices (six sensors in each office). Each multi-sensor device included sensors to measure passive infrared (PIR) radiation, temperature, CO2, humidity, and illuminance. The results show that the positions of PIR and CO2 sensors significantly affect the reliability of occupancy detection. The typical approach of positioning the sensors on the ceiling, in the middle of offices, may lead to relatively unreliable data. In this case, the PIR sensor in that position has only 60% accuracy of presence detection. Installing the sensors under office desks could increase the accuracy of presence detection to 84%. These two sensor positions are highlighted in sensor fusion analysis as they could reach the highest accuracy compared to other pairs of PIR sensors. Moreover, sensor positioning can affect various indoor environmental parameters, especially temperature and illuminance measurements.
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| 5. |
- Rabiee, Ramtin, et al.
(författare)
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LaIF: A Lane-Level Self-Positioning Scheme for Vehicles in GNSS-Denied Environments
- 2019
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Ingår i: IEEE transactions on intelligent transportation systems (Print). - : IEEE. - 1524-9050 .- 1558-0016. ; 20:8, s. 2944-2961
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Tidskriftsartikel (refereegranskat)abstract
- Vehicle self-positioning is of significant importance for intelligent transportation applications. However, accurate positioning (e.g., with lane-level accuracy) is very difficult to obtain due to the lack of measurements with high confidence, especially in an environment without full access to a global navigation satellite system (GNSS). In this paper, a novel information fusion algorithm based on a particle filter is proposed to achieve lane-level tracking accuracy under a GNSS-denied environment. We consider the use of both coarse-scale and fine-scale signal measurements for positioning. Time-of-arrival measurements using the radio frequency signals from known transmitters or roadside units, and acceleration or gyroscope measurements from an inertial measurement unit (IMU) allow us to form a coarse estimate of the vehicle position using an extended Kalman filter. Subsequently, fine-scale measurements, including lane-change detection, radar ranging from the known obstacles (e.g., guardrails), and information from a high-resolution digital map, are incorporated to refine the position estimates. A probabilistic model is introduced to characterize the lane changing behaviors, and a multi-hypothesis model is formulated for the radar range measurements to robustly weigh the particles and refine the tracking results. Moreover, a decision fusion mechanism is proposed to achieve a higher reliability in the lane-change detection as compared to each individual detector using IMU and visual (if available) information. The posterior Cramér-Rao lower bound is also derived to provide a theoretical performance guideline. The performance of the proposed tracking framework is verified by simulations and real measured IMU data in a four-lane highway.
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| 6. |
- Rabiee, Ramtin, et al.
(författare)
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Multi-Bernoulli Tracking Approach for Occupancy Monitoring of Smart Buildings Using Low-Resolution Infrared Sensor Array
- 2021
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Ingår i: Remote Sensing. - : MDPI. - 2072-4292. ; 13:16
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Tidskriftsartikel (refereegranskat)abstract
- Knowledge about the indoor occupancy is one of the important sources of information to design smart buildings. In some applications, the number of occupants in each zone is required. However, there are many challenges such as user privacy, communication limit, and sensor’s computational capability in development of the occupancy monitoring systems. In this work, a people flow counting algorithm has been developed which uses low-resolution thermal images to avoid any privacy concern. Moreover, the proposed scheme is designed to be applicable for wireless sensor networks based on the internet-of-things platform. Simple low-complexity image processing techniques are considered to detect possible objects in sensor’s field of view. To tackle the noisy detection measurements, a multi-Bernoulli target tracking approach is used to track and finally to count the number of people passing the area of interest in different directions. Based on the sensor node’s processing capability, one can consider either a centralized or a full in situ people flow counting system. By performing the tracking part either in sensor node or in a fusion center, there would be a trade off between the computational complexity and the transmission rate. Therefore, the developed system can be performed in a wide range of applications with different processing and transmission constraints. The accuracy and robustness of the proposed method are also evaluated with real measurements from different conducted trials and open-source dataset.
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| 7. |
- Rabiee, Ramtin, et al.
(författare)
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Vehicle localization in GNSS-denied environments
- 2019
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Ingår i: Cooperative localization and navigation. - : CRC Press. - 9781138580619 - 9780429507229 ; , s. 199-222
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Bokkapitel (övrigt vetenskapligt/konstnärligt)abstract
- This chapter discusses possible information sources and methods to fuse the available information to achieve a certain level of tracking precision. It explains the plausible information sources that may aid in vehicular localization. The chapter considers on-board sources, and examines external sources including from the wireless infrastructure as well as from other vehicles. Radar provides distances from objects in their field of view. The likelihood of range measurements from side-scan radars is given by considering the fact that the measured range might be from a known guardrail or from the vehicles in possible adjacent lanes. The assumption of a global navigation satellite system -denied scenario is situational in most cases. Pseudo-range measurements from sharing collected global navigation satellite system (GNSS) data in GNSS-denied environments. The wireless communication between vehicles, and between vehicles and related wireless networks' base stations/infrastructure can be a source of information for the purpose of localization.
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| 8. |
- Song, Yang, et al.
(författare)
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Anchor-free multi-level self-localization in ad-hoc networks
- 2021
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Ingår i: 2021 IEEE Wireless Communications and Networking Conference (WCNC). - : IEEE. - 9781728195056 ; , s. 1-6
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Konferensbidrag (refereegranskat)abstract
- In this paper, we propose a multi-level localization algorithm that breaks a centralized localization problem into a cluster-level distributed localization problem, where each cluster is a centralized unit. In contrast to fully distributed localization, the cluster-level distributed scheme results in reduction in contention, communication overheads, convergence time and energy consumption because cluster heads are responsible for the intracluster positioning on behalf of the whole cluster. To generate a global map, the cluster heads communicate with their direct neighbors to carry out inter-cluster ranging and positioning. The proposed method is suitable for large ad-hoc networks where most agents are low-cost, low-power RF transceivers used for ranging only while some agents are integrated with microcomputers such as Raspberry Pis capable of running intra and inter-cluster localization algorithms. The proposed system can work without anchor nodes and thus it can be deployed in the environments such as urban canyon, inside multi-story buildings, airports, and underground shopping malls where access to anchors or Global Navigation Satellite System (GNSS) is limited or prohibitive. We exploit a hybrid of two well-known methods: multidimensional scaling (MDS) and extended Kalman filtering (EKF) to effectively construct local and global position maps, even in the absence of GNSS information, anchors, or a complete ranging matrix.
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| 9. |
- Yan, Yongsheng, et al.
(författare)
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A tightly coupled integration approach for cooperative positioning enhancement in DSRC vehicular networks
- 2022
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Ingår i: IEEE transactions on intelligent transportation systems (Print). - : IEEE. - 1524-9050 .- 1558-0016. ; 23:12, s. 23278-23294
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Tidskriftsartikel (refereegranskat)abstract
- Intelligent transportation system significantly relies on accurate positioning information of land vehicles for both safety and non-safety related applications, such as hard-braking ahead warning and red-light violation warning. However, existing Global Navigation Satellite System (GNSS) based solutions suffer from positioning performance degradation in challenging environments, such as urban canyons and tunnels. In this paper, we focus on the positioning performance enhancement of land vehicles via cooperative positioning under a partial GNSS environment in a Vehicular Ad-hoc NETwork (VANET). The availability of Time-of-Flight (ToF) based inter-vehicle or vehicle-to-infrastructure ranges is verified via 5.9 GHz Dedicated Short-Range Communication (DSRC) vehicle-to-everything communication with RTS/CTS unicast mechanism. An inertial navigation sensor aided, tightly coupled integration approach for land vehicle cooperative positioning using DSRC ToF ranges and carrier frequency offset range-rates is proposed, where a digital map is used to constrain the position estimates. If available, the GNSS pseudorange and Doppler shift under partial GNSS environment can also be incorporated. A Rao–Blackwellized particle filter is utilized to estimate the unknown variables allowing for reduced computational complexity in comparison with the conventional particle filter. The posterior Cramer–Rao lower bound is also derived to give a theoretical performance guideline. Both simulation and experimental results show the validity of our proposed approach.
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