Turbidity is an important characteristic of water quality that can indicate the presence of undesirable suspended particulate matter. Having access to an inexpensive and effective turbidity sensor unlocks numerous Internet of Things (IoT) possibilities for remote environmental monitoring. Optical light attenuation turbidity sensors operate on the premise of detecting signal degradation from a light source due to scattering from particles in a solution. This approach is technologically unpretentious and only requires a handful of inexpensive electronic components to construct. However, while this method is touted as “simple”, a significant challenge lies in sensor calibration. That is, converting an analogue signal into a meaningful and accurate digital reading in a known turbidity measurement standard (e.g., Nephelometric Turbidity Units (NTU)). This paper presents an IoT light attenuation turbidity sensor design and explores the calibration process to determine the sensor's range and accuracy. Sensor calibration is undertaken using Formazin turbidity standards and is cross-checked against a commercial turbidimeter. We provide a step-by-step procedure for determining the correct signal strength to use and a functional form for the sensor response to the Formazin standard. Finally, we specify an estimate of the accuracy of the sensor and suggest the next steps in the proposed turbidity sensor's development. Results indicate that the sensor achieves within 2%-10% of accuracy at higher ranges (100–4000 NTU), but its performance becomes significantly less reliable in low NTU ranges (< 100 NTU) where the error rate increases to 26%. The turbidity sensor is used as part of an IoT remote aquatic environmental monitoring platform.

The ability to provide near real-time data (e.g., < every 15 minutes) on aquatic environmental conditions via remotely deployed sensors is a highly sought-after capability. However, cost and complexity are often significant factors that limit the spatial and temporal coverage of such monitoring systems. Most existing proposals are expensive, complex and/or are un-malleable for adaptation to other environmental sensing applications. This paper presents a simple and flexible open-source IoT (Internet of Things) electronics design for viable near real-time environmental measurements – specifically tailored to the rigors of aquatic settings. The system provides the minimal required functionality for reliable remote sensor readings with a focus on low energy consumption, renewal energy supply, plug and play deployments, and stability over time. The system development is driven by actual deployment logistics and constraints. We compare three revisions of the system/circuit and show how we aspired towards the aforementioned goals, whilst outlining the evolution of the design based on practical experience. A performance evaluation of the system is given in terms of functionality, stability, cost and energy consumption. The IoT platform is at the core of an affordable near real-time aquatic monitoring system that has been used in multiple water quality studies. The system has been adapted for use in other applications including water height monitoring and air dust sensing.

Shill bidding occurs when fake bids are introduced into an auction on the seller's behalf in order to artificially inflate the final price. This is typically achieved by the seller having friends bid in her auctions, or the seller controls multiple fake bidder accounts that are used for the sole purpose of shill bidding. We previously proposed a reputation system referred to as the Shill Score that indicates how likely a bidder is to be engaging in price inflating behaviour with regard to a specific seller's auctions. A potential bidder can observe the other bidders' Shill Scores, and if they are high, the bidder can elect not to participate as there is some evidence that shill bidding occurs in the seller's auctions. However, if a seller is in collusion with other sellers, or controls multiple seller accounts, she can spread the risk between the various sellers and can reduce suspicion on the shill bidder. Collusive seller behaviour impacts one of the characteristics of shill bidding the Shill Score is examining, therefore collusive behaviour can reduce a bidder's Shill Score. This paper extends the Shill Score to detect shill bidding where multiple sellers are working in collusion with each other. We propose an algorithm that provides evidence of whether groups of sellers are colluding. Based on how tight the association is between the sellers and the level of apparent shill bidding is occurring in the auctions, each participating bidder's Shill Score is adjusted appropriately to remove any advantages from seller collusion. Performance has been tested using simulated auction data and experimental results are presented.

Aquatic environmental sensors are expensive which limits the ability to undertake widescale remote monitoring. In most instances, too much logic and functionality are contained within the sensor device itself. This approach is expensive and computationally restrictive. This paper presents a new architectural paradigm for remotely deployed sensors whereby the calibration logic (and other functionality) is separated from the physical sensor hardware. A sensor device is only responsible for taking raw unprocessed sensor readings, which are transmitted back to a central server. All processing occurs on the server where computational capability and sophistication are unbounded. This approach allows for significant flexibility in terms of dynamic calibration adjustments to be applied to sensor data (e.g., in the case of sensor fouling or device decay) and for statistical quality assurance/data production algorithms to be applied. We present an example of how this paradigm can be adopted in this context to a turbidity sensor.

Turbidity is a key environmental parameter that is used in the determination of water quality. The turbidity of a water body gives an indication of how much suspended sediment is present, which directly impacts the clarity of the water (i.e., whether it is cloudy or clear). Various commercial nephelometric and optical approaches and products exist for electronically measuring turbidity. However, most of these approaches are unsuitable or not viable for collecting data remotely. This paper investigates ways for incorporating a turbidity sensor into an existing remote aquatic environmental monitoring platform that delivers data in near real-time (i.e., 15-min intervals). First, we examine whether an off-the-shelf turbidity sensor can be modified to provide remote and accurate turbidity measurements. Next, we present an inexpensive design for a practical light attenuation turbidity sensor. We outline the sensor’s design rationale and how various technical and physical constraints were overcome. The turbidity sensor is calibrated against a commercial turbidimeter using a Formazin standard. Results indicate that the sensor readings are indicative of actual changes in turbidity, and a calibration curve for the sensor could be attained. The turbidity sensor was trialled in different types of water bodies over nine months to determine the system’s robustness and responsiveness to the environment.

Wireless sensor networks (WSNs) employ middleware solutions to coordinate their sensors and provide web services for managing data. Adding/configuring a new or existing sensor requires modification to the middleware and web service. To integrate hundreds of sensors with different capabilities, a system needs to support all the encodings, models and services for registering, tasking and querying sensors. We present an intelligent agent, which provides automatic semantic-based registration/configuration in a large-scale sensor observation system. The agent can react to any changes internally/externally made (i.e., adding a new sensor or sending a task request to sensors/support systems). The agent makes a 'smart' decision on which system function to use by integrating a semantic representation of sensor network data including middleware and web service specifications and applying logical rules to the knowledge-base. The agent's operation is demonstrated using two real-world systems represented in RDF using a domain ontology that extends the W3C SSN-XG ontology.

Wireless sensor networks are being increasingly used for remote environmental monitoring. Despite advances in technology, there will always be a disparity between the number of competing sensor devices and the amount of network resources available. Auction-based strategies have been used in numerous applications to provide efficient/optimal solutions for determining how to fairly distribute system resources. This paper investigates the suitability of using online auctions to allow sensors to acquire preferential access to network resources. A framework is presented that allocates network priority to sensor devices based on their characteristics such as cost, precision, location, significant changes to readings, and amount of data collected. These characteristics are combined to form the value for a particular sensor's bid in an auction. The sensor with the highest bid wins preferential access to the network. Priority can be dynamically updated over time with regard to these characteristics, changing conditions for the phenomenon under observation, and also with input from a back-end environmental model. We present an example scenario for monitoring a flood's progress down a river to illustrate how the proposed auction-based system operates. A series of simulations were undertaken with a preliminary auction structure to examine how the system functions under different conditions.

Solutions of the combined advection-diffusion-reaction (ADR) transport equation are generally restricted to numerical methods. However, each subprocess, advection, diffusion and reaction can all be solved individually using analytical techniques for a variety of situations. We present a simple numerical technique that uses the split operator method, and the Semi-Lagrangian scheme, to combine these analytical solutions. The result is a coherent, quasi-analytical solution to the combined ADR transport equation. (C) 2015 Elsevier Inc. All rights reserved.

The solution of a Caputo time fractional diffusion equation of order 0<α<1 is expressed in terms of the solution of a corresponding integer order diffusion equation. We demonstrate a linear time mapping between these solutions that allows for accelerated computation of the solution of the fractional order problem. In the context of an N-point finite difference time discretisation, the mapping allows for an improvement in time computational complexity from O(N2) to O(Nα), given a precomputation of O(N1+αln⁡N). The mapping is applied successfully to the least squares fitting of a fractional advection–diffusion model for the current in a time-of-flight experiment, resulting in a computational speed up in the range of one to three orders of magnitude for realistic problem sizes.

Wireless Sensor Networks (WSNs) have been used in numerous applications to remotely gather real-time data on important environmental parameters. There are several projects where WSNs are deployed in different locations and operate independently. Each deployment has its own models, encodings, and services for sensor data, and are integrated with different types of visualization/analysis tools based on individual project requirements. This makes it difficult to reuse these services for other WSN applications. A user/system is impeded by having to learn the models, encodings, and services of each system, and also must integrate/interoperate data from different data sources. Sensor Web Enablement (SWE) provides a set of standards (web service interfaces and data encoding/model specifications) to make sensor data publicly available on the web. This paper describes how the SWE framework can be extended to integrate disparate WSN systems and to support standardized access to sensor data. The proposed system also introduces a web-based data visualization and statistical analysis service for data stored in the Sensor Observation Service (SOS) by integrating open source technologies. A performance analysis is presented to show that the additional features have minimal impact on the system. Also some lessons learned through implementing SWE are discussed.

A given quantity of fill may be placed over a given circular area in the shape of a cone, a truncated cone, with nearly uniform thickness. Depending on the shape of the fill, different non-uniform initial excess pore water pressure distributions can exist in the underlying saturated soil layer. This paper investigates the influence of the shape of the fill on the time-dependant consolidation behaviour of the underlying circular soil layer, which is draining only along a peripheral drain. Plots of the average degree of consolidation against time factor and degree of consolidation isochrones are developed for different axisymmetric embankment geometries. The results show that the way the load is spread within the circular area has significant influence on the rate of pore water pressure dissipation throughout the soil layer. The exact degree of consolidation at a point within the clay is computed to illustrate the variation in the degree of consolidation with the radial distance.

Current database practitioners cannot easily store information about transient phenomena using existing commercial off-the-shelf tools, because vendors do not support temporal database characteristics. This paper describes a practical problem where a relational database must record a series of events that occur over a given time span, without any modification to the underlying database management system. The database must be able to perform queries on the temporal information of an event occurrence. However, the database must also manage overriding events which take precedence over previously scheduled events, while maintaining knowledge of the overridden event. A basic approach to the problem is discussed, which is conceptually simple but cannot efficiently record the required information, nor can it cope with complex overriding event scenarios. We propose a second approach that models the events using time spans. The time span approach is then refined to create a third scheme that can efficiently handle complex overriding event scenarios. The two time span approaches result in significant storage gains compared to the first approach. However, the storage gains come with a trade-off in efficiency for data manipulation queries. The proposed approach is implementable with current relational standards (and SQL), and does not have the overhead and complexity of a full-scale temporal database.

Great care is taken to ensure traditional laboratory consolidation tests operate under one-dimensional conditions. In doing so, restrictions must be imposed upon specimen size (the height to diameter ratio must be less than 0.4), loading setup (the load must be applied vertically and ensure equal strains) and drainage configuration (water must vertically drain through the top and/or bottom of the sample). These restrictions not only severely limit the versatility of an oedometer test, but unnecessarily protract the time required for testing, and only allow determination of the vertical coefficient of consolidation. A three-dimensional consolidation test, however, could significantly shorten this testing time, and allow for evaluation of consolidation anisotropy of the soil (i.e. ratio of horizontal to vertical consolidation coefficients, c(r)/c(v)). Whilst it is relatively straightforward to modify a one-dimensional oedometer test to allow for three-dimensional consolidation, the difficulty lies within the subsequent analysis of settlement-time data, which must be fitted to the theoretical curve corresponding to three-dimensional consolidation. In this paper, the curve-fitting method proposed by Casagrande for evaluation of c(v) from one-dimensional oedometer tests has been extended to allow for three-dimensional consolidation. This method was then used to analyse data from three-dimensional consolidation tests on reconstituted Kaolinite, yielding values for c(r)/c(v) in the range of 0.9 to 2.2, which compare well with the anisotropic properties of Kaolinite reported in literature.

Arching is a phenomenon that occurs in many situations in geotechnical engineering. When underground mine stopes are backfilled, a significant fraction of the self-weight of the backfill is carried by the side walls. As a result, the vertical stress at the bottom of the stope is significantly less than its overburden pressure. Few analytical expressions published in the literature can be used to determine the vertical stresses of stope with parallel walls. The objective of this paper is to extend the analytical solution previously developed by the authors to long plane-strain stopes with non-parallel walls with both slopes leaning to the same side. Different combinations of wall inclination are examined using the new analytical expression developed. To validate the analysis, the proposed results are compared with numerical model results. The results show that the proposed analytical expression is capable of estimating the vertical stress within mine stopes when the inclination of the hangingwall to the horizontal (α) is less than that of footwall (β). An important behavioural trend for the stress distribution is observed, where with the same overburden pressure and base width, the stress magnitude experienced by fill material significantly varies depending on the wall inclination.

— The transfer rate of messages in distributed sensor network applications is a critical factor in a system's performance. The Sensor Abstraction Layer (SAL) is one such system. SAL is a middleware integration platform for abstracting sensor specific technology in order to integrate heterogeneous types of sensors in a network. SAL uses Java Remote Method Invocation (RMI) as its connection method, which has unsatisfying transfer rates, especially for streaming data. This paper analyses different connection methods to optimize data transmission in SAL by replacing RMI. Our results show that the most promising Java-based connections were frameworks for Java New Input/Output (NIO) including Apache MINA, JBoss Netty, and xSocket. A test environment was implemented to evaluate each respective framework based on transfer rate, resource usage, and scalability. Test results showed the most suitable connection method to improve data transmission in SAL JBoss Netty as it provides a performance enhancement of 68%.

The magnitude of consolidation settlement is often calculated using Terzaghi's expression for average degree of consolidation (U) with respect to time. Developed during a time of limited computing capabilities, Terzaghi's series solution to the one-dimensional consolidation equation was generalized using a dimensionless time factor (T), where a single U-T curve is used to describe the consolidation behavior of both singly and doubly drained strata. As a result, any comparisons between one-and two-way drainage are indirect and confined to discrete values of time. By introducing a modified time factor T* in terms of layer thickness (D) instead of the maximum drainage path length (H-dr), it is now possible to observe the effect of drainage conditions over a continuous range of time for a variety of asymmetric initial excess pore pressure distributions. Although two separate U-T plots are required (for singly and doubly drained cases), the time factor at specific times remains the same for both cases, enabling a direct visual comparison. The importance of a revised time factor is evident when observing the endpoint of consolidation, which occurs as U approaches 100%. This occurs at T* congruent to 0.5 for two-way drainage and at T* congruent to 2 for one-way drainage, an observation not possible using the traditional expression for time factor. (C) 2013 American Society of Civil Engineers.

The transfer rate of messages in distributed sensor network applications is a critical factor in a system's performance. The Sensor Abstraction Layer (SAL) is one such system. SAL is a middleware integration platform for abstracting sensor specific technology in order to integrate heterogeneous types of sensors in a network. SAL uses Java Remote Method Invocation (RMI) as its connection method, which has unsatisfying transfer rates, especially for streaming data. This paper analyses different connection methods to optimize data transmission in SAL by replacing RMI. Our results show that the most promising Java-based connections were frameworks for Java New Input/Output (NIO) including Apache MINA, JBoss Netty, and xSocket. A test environment was implemented to evaluate each respective framework based on transfer rate, resource usage, and scalability. Test results showed the most suitable connection method to improve data transmission in SAL JBoss Netty as it provides a performance enhancement of 68%.

Horizontal coefficient of consolidation c(h) is a key parameter in the design of vertical drains and the following consolidation analysis of a soil layer. There are graphical and non-graphical methods available to estimate ch from laboratory radial consolidation tests with a central drain. Currently, the consolidation tests with peripheral drains have to be analysed through a curve fitting method for determining c(h). In this technical note, a non-graphical inflection point method is proposed for determining c(h) for an oedometer test with peripheral drainage, based on the characteristic feature observed when the gradient of the theoretical U-r -log T-r relationship was plotted against T-r. The proposed method is validated through a series of consolidation tests on two reconstituted dredged clay specimens, tested in an oedometer subjected to radial drainage with peripheral drains. The consolidation settlements predicted from the proposed method, for the two different clays, were in excellent agreement with those measured in the oedometer. The proposed method will be a very valuable tool in the analysis of radial consolidation data when the drains are peripheral.

Nonuniform, initial, excess pore-water pressure distributions in the horizontal direction will have a different impact on the consolidation behavior of the soil layer, when compared with the uniform pore-water pressure distributions discussed in the literature. In the current study, various practical instances in which the nonuniform, axisymmetric, horizontal distributions of pore-water pressure occur are identified. The influence of these distribution patterns on the consolidation response of a cylindrical soil layer draining only at its peripheral face is analyzed analytically using a simple series solution method and by finite-element analysis using PLAXIS. From the Uavg-T curves and pore-water pressure isochrones developed, it is observed that the uniform pore-water pressure assumption overestimates the degree of consolidation achieved for various pore-water pressure distribution conditions and important information about pore-water pressure redistribution is overlooked. Incorporating appropriate initial pore-water pressure distribution will enable realistic estimates of the degree of consolidation to be made.

An analytical series solution method for three-dimensional, supercritical flow over topography is presented. Steady, nonlinear solutions are calculated for a single layer of inviscid, constant-density fluid that flows irrotationally over an obstacle that varies significantly in the x-, y- and z-directions. Accurate series solutions for the free surface and a series of stream tubes throughout the flow region are calculated to demonstrate the three-dimensional properties of the problem. These solutions provide valuable insight into the three-dimensional interactions between the fluid and obstacle which is impossible to gain from any two-dimensional model. The model is described by a Laplacian free-boundary problem with fully nonlinear boundary conditions. The solution method consists of iteratively updating the location of the free surface (on top of the fluid) using a cost function which is derived from the Bernoulli equation. Root-mean-square errors in the boundary conditions are used as convergence criteria and a measure of the accuracy of the solution. This method has been used to solve the two-dimensional version of this problem in the past. Here, we detail the extensions required for three-dimensional flow.