The registration problem of thermal images captured from an Unmanned Aerial Vehicle (UAV) is addressed in this paper. After an exhaustive literature review, we conclude that our work is the first to demonstrate that the Scale Invariant Image Transform (SIFT) along with Random Sample Consensus (RANSAC) can successfully be used on thermal images. We contribute an open-source thermal-image registration system that enables UAVs to geolocate hotspots of wildfires. UAVs' measurements of geolocation and cardinal direction have errors, so the location and direction of a hotspot have different values when seen from different UAVs. This paper estimates the geolocation of hotspots by identifying SIFT keypoints on overlapping thermal images, matching the keypoints, and applying a transformation using RANSAC to reconcile the differences among UAVs. We propose image-processing operations including blurring, closing, and opening to enable the successful use of SIFT and RANSAC. Our thermal-image registration system is validated on three datasets. Images of emulated fires were collected using our open-source UAV platform for the first dataset. The other datasets are FLAME and FLAME3, which include images of controlled fires. Our results demonstrate registration and geolocation of hotspots with a success rate of 97%, 90%, and 92% respectively over a total 215 pairs of images.

A measurement technique that decreases the root mean square error (RMSE) of measurements of human-joint angles using a personal wireless sensor network is reported. Its operation is based on virtual rotations of wireless sensors worn by the user, and it focuses on the arm, whose position is measured on 5 degree of freedom (DOF). The wireless sensors use inertial magnetic units that measure the alignment of the arm with the earth's gravity and magnetic fields. Due to the biomechanical properties of human tissue (e.g., skin's elasticity), the sensors' orientation is shifted, and this shift affects the accuracy of measurements. In the proposed technique, the change of orientation is first modeled from linear regressions of data collected from 15 participants at different arm positions. Then, out of eight body indices measured with dual-energy X-ray absorptiometry, the percentage of body fat is found to have the greatest correlation with the rate of change in sensors' orientation. This finding enables us to estimate the change in sensors' orientation from the user's body fat percentage. Finally, an algorithm virtually rotates the sensors using quaternion theory with the objective of reducing the error. The proposed technique is validated with experiments on five different participants. In the DOF, whose error decreased the most, the RMSE decreased from 2.20(°) to 0.87(°). This is an improvement of 60%, and in the DOF whose error decreased the least, the RMSE decreased from 1.64(°) to 1.37(°). This is an improvement of 16%. On an average, the RMSE improved by 44%.

In this paper, a game-theoretical framework for the design of distributed algorithms that control the transmission range (TR) of nodes in order to maximize throughput in Wireless Multihop Networks (WMN) is proposed. It is based on the stability region of the link-scheduling policy adopted for the network. The stability region is defined as the set of input-packet rates under which the queues in the network are stable (i.e., positive recurrent). The goal of the TR-control algorithms is to adapt the stability region to a given set of end-to-end flows. In the algorithms, the flows control distributively the nodes' TRs using the stability region in order to enable higher end-to-end packet rates while guaranteeing stability. In order to demonstrate how the algorithms can be designed using the proposed game-theoretical framework, a new TR-control algorithm for IEEE-802.16 WMNs is developed. Its convergence is demonstrated, and a performance bound is calculated. Finally, simulation results show that the algorithm is able to find the optimal TRs more effectively. The TRs achieve throughput levels that are at least 90 percent of the optimal throughput for 72 percent of the simulated scenarios, whereas the classic approach of spatial-reuse maximization does this for 62 percent of the scenarios.

A major challenge in wireless networks is the ability to maximize the throughput. High throughput in a wireless network requires a relatively low complex scheduling policy with a provable efficiency ratio, which is a measure of the performance of the policy in terms of throughput and stability. For most scheduling policies that achieve provable ratios, at the onset of every frame, a selection is made of a subset of links to transmit data in the immediately following frame. In this paper, we propose a policy that allows links to transmit data in any future frame by means of frame reservations. The new, reservation-based distributed scheduling approach will improve the capacity of the system and provide greater throughput. First, we create a framework to analyze the stability of reservation-based scheduling systems. Then, to demonstrate its efficacy, we propose a reservation-based distributed scheduling policy for IEEE 802.16 mesh networks and use the new framework to find sufficient conditions for the stability of the network under this policy, i.e., we find a lower bound for its efficiency ratio. Finally, by means of simulation, we validate the mathematical analysis and compare the performance of our policy with nonreservation-based policies.

In this paper, we study the problem of transmission power control and its effects on the link-scheduling performance when a set of end-to-end flows established in the network are given. This problem is approached by means of the stability region of the link-scheduling policy. The stability region is defined for link-scheduling policies as the set of input-packet rates under which the queues in the network are stable (i.e., positive recurrent). Specifically, the link-scheduling's stability region is adapted to the paths of the flows such that the flows are able to support higher levels of data traffic under lower levels of end-to-end delay. To the best of our knowledge, the approach of transmission power control based on queue stability has not been studied before. Based on this approach, we propose a transmission-power-control algorithm. It is shown, by means of simulation, that the algorithm outperforms the transmission power control based on spatial reuse.

Several distributed scheduling policies for wireless networks that achieve a provable efficiency ratio have been developed recently. These policies are characterized by the selection, at the onset of every time slot, of a subset of links according to the interference model of the network and the length of the links' queues. The selected subset of links is for the next time slot only. In this paper, we propose a new framework for the stability analysis of distributed scheduling policies that allow links to transmit data packets in any future time slots by means of slot reservations. Within this framework, we propose and analyze a reservation-based distributed scheduling policy for IEEE 802.16 mesh networks. We find sufficient conditions for the stability of the network when the traffic uses one hop. Specifically, we prove a lower bound for its efficiency ratio by evaluating the stability conditions obtained from our proposed framework. Finally, we compare this lower bound with the capacity achieved in simulation results.