Hybrid metaheuristic experiments of real-time adaptive optimization of parametric shading design through remote data transfer

Author(s):  
Hwang Yi
1966 ◽  
Vol 2 (4) ◽  
pp. 135
Author(s):  
A.W. Nicholson ◽  
D.M. Holmes

2021 ◽  
Vol 77 (2) ◽  
pp. 98-108
Author(s):  
R. M. Churchill ◽  
C. S. Chang ◽  
J. Choi ◽  
J. Wong ◽  
S. Klasky ◽  
...  

2012 ◽  
Vol 253-255 ◽  
pp. 705-715 ◽  
Author(s):  
Mohamed Elbanhawi ◽  
Milan Simic

This paper presents one application of industrial robots in the automation of renewable energy production. The robot supports remote performance monitoring and maintenance of salinity gradient solar ponds. The details of the design, setup and the use of the robot sampling station and the remote Data Acquisition (DAQ) system are given here. The use of a robot arm, to position equipment and sensors, provides accurate and reliable real time data needed for autonomous monitoring and control of this type of green energy production. Robot upgrade of solar ponds can be easily integrated with existing systems. Data logged by the proposed system can be remotely accessed, plotted and analysed. Thus the simultaneous and remote monitoring of a large scale network of ponds can be easily implemented. This provides a fully automated solution to the monitoring and control of green energy production operations, which can be used to provide heat and electricity to buildings. Remote real time monitoring will facilitate the setup and operations of several solar ponds around cities.


Author(s):  
VINCENT ROBERGE ◽  
MOHAMMED TARBOUCHI ◽  
FRANÇOIS ALLAIRE

In this paper, we present a parallel hybrid metaheuristic that combines the strengths of the particle swarm optimization (PSO) and the genetic algorithm (GA) to produce an improved path-planner algorithm for fixed wing unmanned aerial vehicles (UAVs). The proposed solution uses a multi-objective cost function we developed and generates in real-time feasible and quasi-optimal trajectories in complex 3D environments. Our parallel hybrid algorithm simulates multiple GA populations and PSO swarms in parallel while allowing migration of solutions. This collaboration between the GA and the PSO leads to an algorithm that exhibits the strengths of both optimization methods and produces superior solutions. Moreover, by using the "single-program, multiple-data" parallel programming paradigm, we maximize the use of today's multicore CPU and significantly reduce the execution time of the parallel program compared to a sequential implementation. We observed a quasi-linear speedup of 10.7 times faster on a 12-core shared memory system resulting in an execution time of 5 s which allows in-flight planning. Finally, we show with statistical significance that our parallel hybrid algorithm produces superior trajectories to the parallel GA or the parallel PSO we previously developed.


1992 ◽  
Vol 82 (1) ◽  
pp. 497-504
Author(s):  
R. W. E. Green

Abstract Observations of teleseismic events at remote sites necessitated the development of a portable digital recorder that is capable of continuously recording the output of a three-component set of long-period transducers. A PC is used as a file management facility, operating in an intermittant or “sleeper mode.” Each of the three components are digitized and stored in separate, intelligent A to D cards. When 28 K samples have been generated, a trigger is initiated, and on the transition of the next real time second the real time is latched and power is applied to the PC. The sample count between the trigger and the latched acknowledgment of the trigger provides an absolute time correlation. After the PC has powered up, the data are down-loaded from the three acquisition cards to a PC hard disk and the latched real time forms the header label of the data file. Power is then removed from the PC. Sampling at about 15 samples per second, the PC is switched on every 33, 45 minutes. Boot-up and data down-loading uses approximately 5 watts average power. The associated long-period transducers (Guralp CMG3) consume about 3 watts and the remaining electronics 2 watts. All the electronics are housed in a steel cabinet, and the system uses four solar panels charging two 105AH batteries. Data transfer to an internal 60 MByte tape streamer necessitates a visit to the station every 24 days.


Author(s):  
Rashima Mahajan ◽  
Pragya Gupta

The progressive research in the field of internet of things provides a platform to develop high performance and robust automated systems to control external devices via internet data transfer and cloud computing. The present emerging IoT research including user-friendly and easily-wearable sensors and signal acquisition techniques have made it possible to expand the IoT application areas towards healthcare sector. This chapter aims at providing a rationale behind development of IoT applications in healthcare, architecture details of internet of healthcare things (IoHT), and highlights a step-by-step development of IoT-based heart rate measurement and monitoring system using Arduino. The developed module has been advanced to transmit data over the internet on the ThingSpeak channel to allow remote monitoring in real time. This may help to improve/restore useful life among cardiac patients via real-time monitoring through remote locations.


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