scholarly journals Cache-Enabled Data Rate Maximization for Solar-Powered UAV Communication Systems

Electronics ◽  
2020 ◽  
Vol 9 (11) ◽  
pp. 1961
Author(s):  
Pham Duy Thanh ◽  
Tran Nhut Khai Hoan ◽  
Hoang Thi Huong Giang ◽  
Insoo Koo
Keyword(s):  
Communication Systems ◽  
Dynamic Environment ◽  
Cost Effective ◽  
Flight Period ◽  
Content Caching ◽  
Rate Maximization ◽  
Markov Decision ◽  
Local Station ◽  
Solar Powered ◽  
Partially Observable

Currently, deploying fixed terrestrial infrastructures is not cost-effective in temporary circumstances, such as natural disasters, hotspots, and so on. Thus, we consider a system of caching-based UAV-assisted communications between multiple ground users (GUs) and a local station (LS). Specifically, a UAV is exploited to cache data from the LS and then serve GUs’ requests to handle the issue of unavailable or damaged links from the LS to the GUs. The UAV can harvest solar energy for its operation. We investigate joint cache scheduling and power allocation schemes by using the non-orthogonal multiple access (NOMA) technique to maximize the long-term downlink rate. Two scenarios for the network are taken into account. In the first, the harvested energy distribution of the GUs is assumed to be known, and we propose a partially observable Markov decision process framework such that the UAV can allocate optimal transmission power for each GU based on proper content caching over each flight period. In the second scenario where the UAV does not know the environment’s dynamics in advance, an actor-critic-based scheme is proposed to achieve a solution by learning with a dynamic environment. Afterwards, the simulation results verify the effectiveness of the proposed methods, compared to baseline approaches.

Multiobjective genetic algorithm to allocate budgetary resources for condition assessment of water and sewer networks1This paper is one of a selection of papers in this Special Issue on Construction Engineering and Management.

2012 ◽  
Vol 39 (9) ◽  
pp. 978-992 ◽  
Author(s):  
Ahmed Atef ◽  
Hesham Osman ◽  
Osama Moselhi
Keyword(s):  
Genetic Algorithm ◽  
Indirect Costs ◽  
Cost Effective ◽  
Condition Assessment ◽  
Multiobjective Genetic Algorithms ◽  
Markov Decision ◽  
The Cost ◽  
Condition State ◽  
Partially Observable ◽  
Computational Platform

This paper presents a framework for optimizing condition assessment policies by balancing the revealed value of information with the cost of obtaining such information. The computational platform is based on augmenting the asset condition state with an expected level of accuracy. Inaccuracies due to condition assessment reliability are evaluated using the partially observable Markov decision process. The single objective genetic algorithm is used to select the most cost-effective assets to assess considering information inaccuracy under a fixed budget. The model is extended using multiobjective genetic algorithms and fuzzy set theory to include minimizing the risk exposure based on asset consequence of failure. This methodology takes into consideration direct and indirect costs of sudden infrastructure failure and reduced level of service costs. A case study is presented using the City of Hamilton, Canada, water network to demonstrate the capabilities of the model.

scholarly journals Integration of satellite system and Stratospheric Communication Platforms (SCP) for weather observation

2016 ◽  
Author(s):  
◽  
Sihle S. Sibiya
Keyword(s):  
High Altitude ◽  
Communication Systems ◽  
Satellite Communication ◽  
Meteorological Data ◽  
Cost Effective ◽  
Satellite System ◽  
Satellite Systems ◽  
Observation Area ◽  
Solar Powered ◽  
Weather Observation

This doctoral research introduces an integration of satellite systems and new stratospheric platforms for weather observation, imaging and transfer of meteorological data to the ground infrastructures. Terrestrial configuration and satellite communication subsystems represent well-established technologies that have been involved in global satellite sensing and weather observation area for years. However, in recent times, a new alternative has emerged based on quasi-stationary aerial platforms located in the Stratosphere called High Altitude Platform (HAP) or Stratospheric Communication Platforms (SCP). The SCP systems seem to represent a dream come true for communication engineers since they preserve most of the advantages of both terrestrial and satellite communication systems. Today, SCP systems are able to help, in a more cost effective way, developments of space Earth sensing and weather observation and weather sensing and observation. This new system can provide a number of forms ranging from a low altitude tethered balloon to a high altitude (18 – 25 km) fuel-powered piloted aircraft, solar-powered unmanned airplanes and solar-powered airship.

scholarly journals UAV Framework for Autonomous Onboard Navigation and People/Object Detection in Cluttered Indoor Environments

2020 ◽  
Vol 12 (20) ◽  
pp. 3386
Author(s):  
Juan Sandino ◽  
Fernando Vanegas ◽  
Frederic Maire ◽  
Peter Caccetta ◽  
Conrad Sanderson ◽  
...  
Keyword(s):  
Autonomous Navigation ◽  
Communication Systems ◽  
Satellite System ◽  
Human Operator ◽  
Indoor Environments ◽  
Flight Operations ◽  
Markov Decision ◽  
Indoor Scenarios ◽  
Global Navigation Satellite ◽  
Partially Observable

Response efforts in emergency applications such as border protection, humanitarian relief and disaster monitoring have improved with the use of Unmanned Aerial Vehicles (UAVs), which provide a flexibly deployed eye in the sky. These efforts have been further improved with advances in autonomous behaviours such as obstacle avoidance, take-off, landing, hovering and waypoint flight modes. However, most UAVs lack autonomous decision making for navigating in complex environments. This limitation creates a reliance on ground control stations to UAVs and, therefore, on their communication systems. The challenge is even more complex in indoor flight operations, where the strength of the Global Navigation Satellite System (GNSS) signals is absent or weak and compromises aircraft behaviour. This paper proposes a UAV framework for autonomous navigation to address uncertainty and partial observability from imperfect sensor readings in cluttered indoor scenarios. The framework design allocates the computing processes onboard the flight controller and companion computer of the UAV, allowing it to explore dangerous indoor areas without the supervision and physical presence of the human operator. The system is illustrated under a Search and Rescue (SAR) scenario to detect and locate victims inside a simulated office building. The navigation problem is modelled as a Partially Observable Markov Decision Process (POMDP) and solved in real time through the Augmented Belief Trees (ABT) algorithm. Data is collected using Hardware in the Loop (HIL) simulations and real flight tests. Experimental results show the robustness of the proposed framework to detect victims at various levels of location uncertainty. The proposed system ensures personal safety by letting the UAV to explore dangerous environments without the intervention of the human operator.

Optimal adaptive inspection and maintenance for redundant systems

2021 ◽  
pp. 1748006X2110201
Author(s):  
Chaochao Lin ◽  
Matteo Pozzi
Keyword(s):  
Engineering Systems ◽  
Discounted Cost ◽  
Markov Decision ◽  
Inspection And Maintenance ◽  
And Performance ◽  
Partially Observable ◽  
Series Systems ◽  
Selection Of ◽  
Redundant Systems

Optimal exploration of engineering systems can be guided by the principle of Value of Information (VoI), which accounts for the topological important of components, their reliability and the management costs. For series systems, in most cases higher inspection priority should be given to unreliable components. For redundant systems such as parallel systems, analysis of one-shot decision problems shows that higher inspection priority should be given to more reliable components. This paper investigates the optimal exploration of redundant systems in long-term decision making with sequential inspection and repairing. When the expected, cumulated, discounted cost is considered, it may become more efficient to give higher inspection priority to less reliable components, in order to preserve system redundancy. To investigate this problem, we develop a Partially Observable Markov Decision Process (POMDP) framework for sequential inspection and maintenance of redundant systems, where the VoI analysis is embedded in the optimal selection of exploratory actions. We investigate the use of alternative approximate POMDP solvers for parallel and more general systems, compare their computation complexities and performance, and show how the inspection priorities depend on the economic discount factor, the degradation rate, the inspection precision, and the repair cost.

Solar Thermophotovoltaic Converters Based on Tungsten Emitters

2006 ◽  
Vol 129 (3) ◽  
pp. 298-303 ◽  
Author(s):  
V. M. Andreev ◽  
A. S. Vlasov ◽  
V. P. Khvostikov ◽  
O. A. Khvostikova ◽  
P. Y. Gazaryan ◽  
...  
Keyword(s):  
Band Gap ◽  
High Efficiency ◽  
Radiation Spectrum ◽  
Cost Effective ◽  
Fresnel Lens ◽  
Photocurrent Density ◽  
Back Side ◽  
High Concentration ◽  
Emitter System ◽  
Solar Powered

Results of a solar thermophotovoltaic (STPV) system study are reported. Modeling of the STPV module performance and the analysis of various parameters influencing the system are presented. The ways for the STPV system efficiency to increase and their magnitude are considered such as: improvement of the emitter radiation selectivity and application of selective filters for better matching the emitter radiation spectrum and cell photoresponse; application of the cells with a back side reflector for recycling the sub-band gap photons; and development of low-band gap tandem TPV cells for better utilization of the radiation spectrum. Sunlight concentrator and STPV modules were designed, fabricated, and tested under indoor and outdoor conditions. A cost-effective sunlight concentrator with Fresnel lens was developed as a primary concentrator and a secondary quartz meniscus lens ensured the high concentration ratio of ∼4000×, which is necessary for achieving the high efficiency of the concentrator–emitter system owing to trap escaping radiation. Several types of STPV modules have been developed and tested under concentrated sunlight. Photocurrent density of 4.5A∕cm2 was registered in a photoreceiver based on 1×1cm2GaSb cells under a solar powered tungsten emitter.

POMDP-Based Coding of Child–Robot Interaction within a Robot-Assisted ASD Diagnostic Protocol

2018 ◽  
Vol 15 (02) ◽  
pp. 1850011 ◽  
Author(s):  
Frano Petric ◽  
Damjan Miklić ◽  
Zdenko Kovačić
Keyword(s):  
Humanoid Robots ◽  
Autism Diagnostic Observation Schedule ◽  
Autism Spectrum ◽  
Diagnostic Process ◽  
Sequential Decision ◽  
Robot Assisted ◽  
Robot Interaction ◽  
Fine Grained ◽  
Markov Decision ◽  
Partially Observable

The existing procedures for autism spectrum disorder (ASD) diagnosis are often time consuming and tiresome both for highly-trained human evaluators and children, which may be alleviated by using humanoid robots in the diagnostic process. Hence, this paper proposes a framework for robot-assisted ASD evaluation based on partially observable Markov decision process (POMDP) modeling, specifically POMDPs with mixed observability (MOMDPs). POMDP is broadly used for modeling optimal sequential decision making tasks under uncertainty. Spurred by the widely accepted autism diagnostic observation schedule (ADOS), we emulate ADOS through four tasks, whose models incorporate observations of multiple social cues such as eye contact, gestures and utterances. Relying only on those observations, the robot provides an assessment of the child’s ASD-relevant functioning level (which is partially observable) within a particular task and provides human evaluators with readable information by partitioning its belief space. Finally, we evaluate the proposed MOMDP task models and demonstrate that chaining the tasks provides fine-grained outcome quantification, which could also increase the appeal of robot-assisted diagnostic protocols in the future.

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