Wenyan Wu

Efficient Object Localization Using Sparsely Distributed Passive RFID Tags

Radio-frequency identification (RFID) technology has been widely used in passive RFID localization application due to its flexible deployment and low cost. However, current passive RFID localization systems cannot achieve both highly accurate and precise moving object localization task owing to tag collisions and variation of the behavior of tags. Most researchers increase the density of tag distribution to improve localization accuracy and then consider using either anti-collision process embedded in the hardware of the RFID reader or advanced localization algorithms to enhance localization precision. However, advanced anti-collision processes for RFID devices are challenged by the physical constraint characteristics of radio frequency; and improved localization algorithm cannot fundamentally reduce the impacts of tag collision on localization precision. This research work attempts to improve localization precision of a passive RFID localization system by using sparsely distributed RFID tags. This paper first defines a measure for accuracy and precision in a passive RFID localization system with regard to RFID tag distribution. An exponential-based function is then derived from experimental measurements, which reflects the relationship between RFID tag distribution and localization precision. This function shows that localization precision is mainly determined by tag density of RFID tag distribution. Based on the experimental findings, a sparse RFID tag distribution approach is proposed. The results show that in comparison with the conventional RFID tag distribution, passive RFID localization system with sparse RFID tag distribution can deliver a higher localization precision for the required accuracy.

Accounting for Greenhouse Gas Emissions in Multiobjective Genetic Algorithm Optimization of Water Distribution Systems

Considerable research has been carried out on the optimization of water distribution systems WDSs over the last three decades. In previous research, attention has mainly focused on the minimization of cost, due to the high expenditure associated with the construction and maintenance of such systems. However, the impacts of WDSs on the environment usually have not been considered adequately. The recent increasing awareness of sustainability and climate change, especially global warming, has led to research where greenhouse gas GHG emissions are considered. In the study described in this paper a multiobjective genetic algorithm for WDS optimization has been used as an explorative tool to investigate the trade-offs between the traditional economic objective of minimizing costs and an additional environmental objective of minimizing GHG emissions. The impacts of minimizing GHG emissions on the results of WDS optimization have been explored for a case study in this paper. The results indicate that the inclusion of GHG emission minimization as one of the objectives results in significant trade-offs between the economic and environmental objectives. Furthermore, a sensitivity analysis has been conducted by using different discount rates in a present value analysis for computing both ongoing costs and GHG emissions. The results obtained show that the Pareto-optimal front is very sensitive to the discount rates used. As a result, the selection of discount rates has a significant impact on final decision making.

Review: Protocol for developing ANN models and its application to the assessment of the quality of the ANN model development process in drinking water quality modelling

The application of Artificial Neural Networks (ANNs) in the field of environmental and water resources modelling has become increasingly popular since early 1990s. Despite the recognition of the need for a consistent approach to the development of ANN models and the importance of providing adequate details of the model development process, there is no systematic protocol for the development and documentation of ANN models. In order to address this shortcoming, such a protocol is introduced in this paper. In addition, the protocol is used to critically review the quality of the ANN model development and reporting processes employed in 81 journal papers since 2000 in which ANNs have been used for drinking water quality modelling. The results show that model architecture selection is the best implemented step, while greater focus should be given to input selection considering input independence and model validation considering replicative and structural validity.

Single-objective versus multiobjective optimization of water distribution systems accounting for greenhouse gas emissions by carbon pricing.

Previous research has demonstrated that there are significant trade-offs between the competing objectives of minimizing costs and greenhouse gas (GHG) emissions for water distribution system (WDS) optimization. However, upon introduction of an emission trading scheme, GHG emissions are likely to be priced at a particular level. Thus, a monetary value can be assigned to GHG emissions, enabling a single-objective optimization approach to be used. This raises the question of whether the introduction of carbon pricing under an emission trading scheme will make the use of a multiobjective optimization approach obsolete or whether such an approach can provide additional insights that are useful in a decision-making context. In this paper, the above questions are explored via two case studies. The optimization results obtained for the two case studies using both single-objective and multiobjective approaches are analyzed. The analyses show that the single-objective approach results in a loss of trade-off informa...

Battle of the Water Networks II

The Battle of the Water Networks II (BWN-II) is the latest of a series of competitions related to the design and operation of water distribution systems (WDSs) undertaken within the Water Distribution Systems Analysis (WDSA) Symposium series. The BWN-II problem specification involved a broadly defined design and operation problem for an existing network that has to be upgraded for increased future demands, and the addition of a new development area. The design decisions involved addition of new and parallel pipes, storage, operational controls for pumps and valves, and sizing of backup power supply. Design criteria involved hydraulic, water quality, reliability, and environmental performance measures. Fourteen teams participated in the Battle and presented their results at the 14th Water Distribution Systems Analysis conference in Adelaide, Australia, September 2012. This paper summarizes the approaches used by the participants and the results they obtained. Given the complexity of the BWN-II problem and the innovative methods required to deal with the multiobjective, high dimensional and computationally demanding nature of the problem, this paper represents a snap-shot of state of the art methods for the design and operation of water distribution systems. A general finding of this paper is that there is benefit in using a combination of heuristic engineering experience and sophisticated optimization algorithms when tackling complex real-world water distribution system design problems

Efficient Particle Filter Localization Algorithm in Dense Passive RFID Tag Environment

The means of distributing dense passive radio-frequency identification (RFID) tags has been widely utilized for accurate indoor localization. However, they suffer a disadvantage on low localization precision due to the increasing interference of RFID tag collisions and the variation of behavior of tags. Current localization algorithms used in passive RFID location systems are mostly deterministic and have a limited capability on improving localization precision in a dynamic environment with uncertain sensor measurement. This paper investigates the feasibility of using particle filter technique as an efficient localization approach to deliver both relatively good accuracy and precision in dense passive RFID tag distribution applications. A position feature-based system model is first built to apply the typical particle filter technique in passive RFID location applications. Then, a new particle filter algorithm by using a moving direction estimation-based feature improvement scheme is proposed to enhance localization precision in a dense passive RFID tag environment. Experimental results show that the proposed method can provide relatively good accuracy and precision for passive RFID location applications, with an improved performance over the typical particle filter algorithm and a state-of-the-art deterministic method.

Incorporation of variable-speed pumping in multiobjective genetic algorithm optimization of the design of water transmission systems

AbstractGlobal warming caused by human activities presents serious global risks. Individuals, governments, and industries need to be more energy efficient and contribute to the mitigation of global warming by reducing their greenhouse gas (GHG) emissions. In previous research, GHG emission reduction has been identified as one important criterion in improving the sustainability of urban infrastructure and urban water systems. Within the water industry, opportunities exist for reducing GHG emissions by improving pumping efficiency via the use of variable-speed pumps (VSPs). Previously, VSPs have been used in the optimization of the operation of existing water distribution systems (WDSs). However, in WDS design optimization problems, fixed-speed pumps (FSPs) are commonly used. In this study, a pump power estimation method, developed using a false position method based optimization approach, is proposed to incorporate VSPs in the conceptual design or planning of water transmission systems (WTSs), using optimi...

Power harvesting for smart sensor networks in monitoring water distribution system

Recently, there has been a growing interest in using wireless sensor networks for monitoring water distribution infrastructure to help drinking water utilities to have better understanding of hydraulic and water quality statement of their underground assets. One of the challenges is limited power resources for operating the smart sensors and sensor networks. Current common used power supplies for sensor node are batteries. Batteries have many drawbacks such as short life time and need to be replaced on regular basis which is uneconomical and unmanageable in hard access environment such as buried underground water pipelines. Energy harvesting of ambient energy in the water pipeline and powering wireless sensor node including sensing, processing, and communications would be particularly attractive option because the life time of the node will be potentially infinite for supporting wireless sensor networks. The paper will review and discuss the potential of using power harvesting techniques for monitoring water distribution networks and the work done in the area of monitoring water distribution systems using smart sensor networks.

Sensitivity of Optimal Tradeoffs between Cost and Greenhouse Gas Emissions for Water Distribution Systems to Electricity Tariff and Generation

Increased awareness of climate change has shifted the focus of water distribution system (WDS) optimization research from cost minimization only to the incorporation of energy or associated greenhouse gas (GHG) minimization. In this study, a sensitivity analysis is conducted to investigate the effect of electricity tariff and generation (emission factors) on the results of multiobjective WDS optimization accounting for both total economic cost (both capital and operating costs) and GHGs. A multiobjective genetic algorithm-based optimization approach is used to conduct the analysis. The results show that electricity tariff has a significant effect on the total economic cost of WDSs and the selection of optimal solutions. In contrast, the changes of emission factors in the future have a significant effect on the total GHGs from WDSs. However, it does not alter the final solutions on the Pareto-optimal front. DOI: 10.1061/(ASCE)WR.1943-5452.0000169.

WATER DISTRIBUTION SYSTEM OPTIMISATION ACCOUNTING FOR A RANGE OF FUTURE POSSIBLE CARBON PRICES

Climate change, especially global warming caused by human activities presents serious global risks. Mitigating global warming by reducing greenhouse gas (GHG) emissions is a unique challenge facing our generation. In order to tackle this challenge, many measures are being developed, among which carbon trading is a popular one. In this paper, a new paradigm for the design of water distribution systems (WDSs) is being developed under a possible emission trading scheme. In this paradigm, minimisation of the costs of GHG emissions is incorporated into the optimisation of WDSs either as one part of the objective or as a second objective. A multi-objective genetic algorithm (MOGA) called WSMGA (water system multi-objective genetic algorithm) has been developed to solve this problem. The time value of both the system costs and the costs from GHG emissions has been taken into account by using present value analysis. Following the Stern Review Report there is controversy as to what discount rate should be used in present value analysis for mitigation of climate change, consequently two different discount rates have been used in this study. The impacts that the carbon prices used in the emission trading scheme have on the optimisation of WDSs have been explored for two hypothetical case studies. The optimisation results show that the different carbon prices used lead to different solutions in the single-objective optimisation formulation. In general, a network with larger pipes is chosen when a higher carbon price is used. In contrast, the carbon price used has no impact on the multi-objective optimisation results. However, different carbon prices lead to different amounts of savings in greenhouse gas costs resulting from the same amount of increase in system costs for the same ordered set of Paretooptimal solutions.