我的台灣, 看見心靈的故鄉 =2009林磐聳藝術與設計展

Energy harvesting from pavements and roadways: A comprehensive review of technologies, materials, and challenges

Fabrication and performance of a power generation device based on stacked piezoelectric energy-harvesting units for pavements

Optimization design and experimental investigation of piezoelectric energy harvesting devices for pavement

Watts-level road-compatible piezoelectric energy harvester for a self-powered temperature monitoring system on an actual roadway

This paper presents a technical simulation based system to support the concept of generating energy from road traffic using piezoelectric materials. The simulation based system design replicates a real life system implementation. It investigates practicality and feasibility using a real-time simulation platform known as MATLAB-Simulink. The system design structure was proposed considering factors involved with the field of material sciences for piezoelectric generator modeling and field of power electronics for additional components in producing a realist outcome. It also ensures ease of vehicle performance, as this system utilizes energy source derived as kinetic energy released from vehicles into electrical power output, that is, obtained by harnessing kinetic energy due to strain of vehicles over asphalt road surface. Due to the real-time simulation platform, the system simulation predicts the effective global carbon footprint. In addition to evaluating technical viability, a technoeconomical business analysis provides a strategic perspective. By using the simulation based power generation results, an estimation of implementation cost and payback time in real life (for United Arab Emirates) was derived, hence validating and predicting real-time economic outcome. This is followed by a comparative study with other sources of renewable energy based on levelized energy cost factor that justifies the performance of the proposed system over other renewable energy sources, in support of providing an economical solution on reducing global carbon footprint.

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Piezoelectric Energy Generation from Vehicle Traffic with Technoeconomic Analysis

This article investigates various existing piezoelectric materials and the structures of the piezoelectric transducers. Then the article explores the idea of using the electricity generated using piezoelectric elements and compares the energy requirement of this era of power electronics. Then, the most compatible piezoelectric transducer for producing sustainable energy from the road traffic was analyzed using the finite element analysis. This included the various structural designs of the piezoelectric harvester designs to determine the performance of the piezoelectric material. The structures focused on this article are namely the Pile type, Multilayered, Thunder, Bridge, Cymbal and Moonie piezoelectric generators. The finite element analysis was also used to categorize the chemical behavior of various piezoelectric elements. After which, the article focuses on the two main types of implementation of the piezoelectric generators on the road to produce the sustainable form of energy. This energy is captured by harnessing the wasted vibration and kinetic energy due to the moving vehicles on the surface of the road. These two main types of implementation include the cantilever beam type implementation such as the bimorph with a tip mass, which requires a fixed support. The other implementation was based on embedding the piezoelectric transducers into the road to harvest the strain and kinetic energy due to the vehicles directly.

Investigation on the Selection of Piezoelectric Materials for the Design of an Energy Harvester System to Generate Energy from Traffic

Fire-fighting robots are used in indoor environments to detect fires and extinguish them. Sensors such as flame sensors are currently used to detect fire in fire-fighting robots. The disadvantage of using sensors is that fire beyond a threshold distance cannot be detected. Using artificial intelligence techniques, fire can be detected in a wider range. Haar Cascade Classifier is a machine-learning algorithm that was initially used for object detection. The results obtained using Haar Cascade Classifier were not very accurate, especially when multiple fires had to be detected. Transfer learning from a pretrained YOLOv3 model was then used to train the model for fire detection to improve accuracy. The benefits and drawbacks of using deep learning for object detection over machine learning are highlighted. The algorithm used to obtain the target location the robot must move to use bounding box coordinates is also discussed in this paper.

Fire Detection using Artificial Intelligence for Fire-Fighting Robots

In this era of a politically unstable world, there is a growing demand for the use of military robots to aid the soldiers to perform perilous missions This paper focuses on the design and build of a semi-autonomous, unmanned robotic system used for various military and rescue operations Dangerous tasks such as bomb disposal, enemy territory surveillance, search and rescue can be efficiently carried out by the MSRR, Military Support and Rescue Robot This reduces the risk of losing the lives of both soldiers and civilians With the help of live feed from the wireless camera and data analysis of environmental composition by various sensors, of the area under surveillance, the soldiers can better prepare for their missions Using Arduino and Zigbee technology, the above-mentioned tasks can be achieved The different sensors and the robotic arm are connected to the Arduino mega which in turn is connected to the Zigbee Data transmission and receiving are through Zigbee technology This prototype design overcomes the weakness of the existing models and thus provides better support for military operations

Military Support and Rescue Robot

The recent shift towards the utilisation of automated systems has necessitated newer and more advanced technologies that can improve efficiency, accuracy and flexibility of processes in the industrial environment. The focus of this paper is on remote monitoring and automation for Bottle filling industry using Supervisory Control and Data Acquisition (SCADA) systems. Effective storage and management of the packaged bottles (warehouse management systems) has also been illustrated through a comparative study between two warehouse management techniques using Barcode technology and crane automation systems. The optimisation of warehouse activities can further increase the consistency and efficiency of the industry. Implementation has been carried using Programmable Logic Controller (PLC) – SCADA systems which provides durability, flexibility and ease of programming. This system can be further expanded into any other sorting industries as well.

Senthil Arumugam Muthukumaraswamy

Papers

Piezoelectric Energy Generation from Vehicle Traffic with Technoeconomic Analysis

Investigation on the Selection of Piezoelectric Materials for the Design of an Energy Harvester System to Generate Energy from Traffic

Fire Detection using Artificial Intelligence for Fire-Fighting Robots

Military Support and Rescue Robot

Design and Development of Industrial Automated System using PLC-SCADA