RFID based Efficient Lighting Control

The Kyoto Protocol and the European Energy Performance of Buildings Directive put an onus on governments
and organisations to lower carbon footprint in order to contribute towards reducing global warming. A key
parameter to be considered in buildings towards energy and cost savings is its indoor lighting that has a major
impact on overall energy usage and Carbon Dioxide emissions. Lighting control in buildings using Passive
Infrared sensors is a reliable and well established approach; however, the use of only Passive Infrared does not
offer much savings towards reducing carbon, energy, and cost. Accurate occupancy monitoring information can
greatly affect a building’s lighting control strategy towards a greener usage. This paper presents an approach for
data fusion of Passive Infrared sensors and passive Radio Frequency Identification (RFID) based occupancy
monitoring. The idea is to have efficient, need-based, and reliable control of lighting towards a green indoor
environment, all while considering visual comfort of occupants. The proposed approach provides an estimated
13% electrical energy savings in one open-plan office of a University building in one working day. Practical
implementation of RFID gateways provide real-world occupancy profiling data to be fused with Passive
Infrared sensing towards analysis and improvement of building lighting usage and control.

Development of M13 bacteriophage-based SPR detection using Salmonella detection as a case study

Surface plasmon resonance (SPR)-based biosensor is a popular platform for real-time monitoring and sensitive detection for a myriad of targets. However, only a few studies have reported the use of bacteriophages as specific binders for SPR-based detection. This study aimed to demonstrate how filamentous M13 bacteriophages expressing 12-mer peptides can be employed in an SPR-based assay, using a Salmonella-specific bacteriophage as a model binder to detect the foodborne bacterium Salmonella. Several important factors (immobilization buffers and methods, and interaction buffers) for a successful bacteriophage-based SPR assay were optimized. As a result, a Salmonella-specific bacteriophage-based SPR assay was achieved, with very low cross reactivity with other non-target foodborne pathogens and detection limits of 8.0 × 10⁷ and 1.3 × 10⁷ CFU/mL for one-time and five-time immobilized sensors, respectively. This proof-of-concept study demonstrates the feasibility of using M13 bacteriophages expressing target-specific peptides as a binder in a rapid and label-free SPR assay for pathogen detection.

Electrochemical sensor for catechol and dopamine based on a catalytic molecularly imprinted polymer-conducting polymer hybrid recognition element

One of the difficulties with using molecularly imprinted polymers (MIPs) and other electrically insulating materials as the recognition element in electrochemical sensors is the lack of a direct path for the conduction of electrons from the active sites to the electrode. We have sought to address this problem through the preparation and characterization of novel hybrid materials combining a catalytic MIP, capable of oxidizing the template, catechol, with an electrically conducting polymer. In this way a network of "molecular wires" assists in the conduction of electrons from the active sites within the MIP to the electrode surface. This was made possible by the design of a new monomer that combines orthogonal polymerizable functionality; comprising an aniline group and a methacrylamide. Conducting films were prepared on the surface of electrodes (Au on glass) by electropolymerization of the aniline moiety. A layer of MIP was photochemically grafted over the polyaniline, via N,N'-diethyldithiocarbamic acid benzyl ester (iniferter) activation of the methacrylamide groups. Detection of catechol by the hybrid-MIP sensor was found to be specific, and catechol oxidation was detected by cyclic voltammetry at the optimized operating conditions: potential range -0.6 V to +0.8 V (vs Ag/AgCl), scan rate 50 mV/s, PBS pH 7.4. The calibration curve for catechol was found to be linear to 144 µM, with a limit of detection of 228 nM. Catechol and dopamine were detected by the sensor, whereas analogues and potentially interfering compounds, including phenol, resorcinol, hydroquinone, serotonin, and ascorbic acid, had minimal effect (=3%) on the detection of either analyte. Nonimprinted hybrid electrodes and bare gold electrodes failed to give any response to catechol at concentrations below 0.5 mM. Finally, the catalytic properties of the sensor were characterized by chronoamperometry and were found to be consistent with Michaelis-Menten kinetics. © 2009 American Chemical Society.

Fluorescence based fibre optic pH sensor for the pH 10–13 range suitable for corrosion monitoring in concrete structures

The design, development and evaluation of an optical fibre pH sensor for monitoring pH in the alkaline region are discussed in detail in this paper. The design of this specific pH sensor is based on the pH induced change in fluorescence intensity of a coumarin imidazole dye which is covalently attached to a polymer network and then fixed to the distal end of an optical fibre. The sensor provides a response over a pH range of 10.0–13.2 with an acceptable response rate of around 50 min, having shown a very good stability over a period of longer than 20 months thus far. The sensor has also demonstrated little cross-sensitivity to ionic strength (IS) and also excellent photostability through a series of laboratory tests. These features make this type of sensor potentially well suited for in situ long term monitoring of pH in concrete structures, to enhance structural monitoring in the civil engineering sector

Modification of Fluorescent Photoinduced Electron Transfer (PET) Sensors/Switches To Produce Molecular Photo-Ionic Triode Action

The fluorophore-spacer₁-receptor₁-spacer₂-receptor₂ system (where receptor₂ alone is photoredox-inactive) shows ionically tunable proton-induced fluorescence off-on switching, which is reminiscent of thermionic triode behavior. This also represents a new extension to modular switch systems based on photoinduced electron transfer (PET) towards the emulation of analogue electronic devices.

Taking Baby Steps in Molecular Logic-based Computation

Molecular logic-based computation is a broad umbrella covering molecular sensors at its simplest level and logic gate arrays involving steadily increasing levels of parallel and serial integration. The fluorescent PET(photoinduced electron transfer) switching principle remains a loyal servant of this entire field. Applications arise from the convenient operation of molecular information processors in very small spaces.

Microelectrode Voltammetry of Dioxygen Reduction in a Phosphonium Cation-Based Room-Temperature Ionic Liquid: Quantitative Studies

Microelectrode voltammetry is used to study the electrochemical reduction of dioxygen, O-2, in the room-temperature ionic liquid trihexyl(tetradecyl)phosphonium trifluorotris(pentafluoroethyl)phosphate [P6,6,6,14][FAP]. The nature of the unusual voltammetric waves is quantitatively modeled via digital simulation with the aim of clarifying apparent inconsistencies in the literature. The reduction is shown to proceed via a two-electron reaction and involve the likely capture of a proton from the solvent system. The oxidative voltammetric signals seen at fast scan rates are interpreted as resulting from the reoxidation of HO2 center dot. In the presence of large amounts of dissolved carbon dioxide the reductive currents decrease by a factor of ca. two, consistent with the trapping of the superoxide radical, O-2(center dot), intermediate in the two-electron reduction process.

A multi-capability sensor for hydrocarbons, synthetic-based fluids and heavy metals:Applications for environmental monitoring during removal of drill cuttings piles

As part of any drilling cuttings pile removal process the requirement for monitoring the release of contaminants into the marine environment will be critical. Traditional methods for such monitoring involve taking samples for laboratory analysis. This process is time consuming and only provides data on spot samples taken from a limited number of locations and time frames. Such processes, therefore, offer very restricted information. The need for improved marine sensors for monitoring contaminants is established. We report here the development and application of a multi-capability optical sensor for the real-time in situ monitoring of three key marine environmental and offshore/oil parameters: hydrocarbons, synthetic-based fluids and heavy metal concentrations. The use of these sensors will be a useful tool for real-time in situ environmental monitoring during the process of decommissioning offshore structures. Multi-capability array sensors could also provide information on the dispersion of contamination from drill cuttings piles either while they are in situ or during their removal.

AgriSense: Multichannel disposable sensors for animal health disease diagnostics

Rapid and sensitive detection of viral infections associated with Bovine Respiratory Disease (BRD) in live animals is recognized as key to minimizing the impact of this disease. ELISA-based testing is limited as it typically relies on the detection of a single viral antibody subtype within an individual test sample and testing is relatively slow and expensive. We have recently initiated a new project entitled AgriSense to develop a novel low-cost and label-free, integrated bimodal electronic biosensor system for BRD. The biosensor system will consist of an integrated multichannel thin-film-transistor biosensor and an electrochemical impedance spectroscopy biosensor, interfaced with PDMS-based microfluidic sample delivery channels. By using both sensors in tandem, nonspecific binding biomolecules must have the same mass to charge ratio as the target analyte to elicit equivalent responses from both sensors. The system will target simultaneous multiplexed sensing of the four primary viral agents involved in the development of BRD: bovine herpesvirus-1 (BHV-1), bovine parainfluenza virus-3 (BPIV-3), bovine respiratory syncytial virus (BRSV), and bovine viral diarrhea (BVD). Optimized experimental conditions derived through model antigen-antibody studies will be applied to the detection of serological markers of BRD-related infections based on IgG interaction with a panel of sensor-immobilized viral proteins. This rapid, “cowside” multiplex sensor capability presents a major step forward in disease diagnosis, helping to ensure the integrity of the agri-food supply chain by reducing the risk of disease spread during animal movement and transport.

Blind Characterisation of Sensors with Second-Order Dynamic Response

Compensation for the dynamic response of a temperature sensor usually involves the estimation of its input on the basis of the measured output and model parameters. In the case of temperature measurement, the sensor dynamic response is strongly dependent on the measurement environment and fluid velocity. Estimation of time-varying sensor model parameters therefore requires continuous textit{in situ} identification. This can be achieved by employing two sensors with different dynamic properties, and exploiting structural redundancy to deduce the sensor models from the resulting data streams. Most existing approaches to this problem assume first-order sensor dynamics. In practice, however second-order models are more reflective of the dynamics of real temperature sensors, particularly when they are encased in a protective sheath. As such, this paper presents a novel difference equation approach to solving the blind identification problem for sensors with second-order models. The approach is based on estimating an auxiliary ARX model whose parameters are related to the desired sensor model parameters through a set of coupled non-linear algebraic equations. The ARX model can be estimated using conventional system identification techniques and the non-linear equations can be solved analytically to yield estimates of the sensor models. Simulation results are presented to demonstrate the efficiency of the proposed approach under various input and parameter conditions.

Novel titania sol-gel derived film for luminescence-based oxygen sensing.

A novel method for the preparation of titania sol–gel derived oxygen sensors based on the ruthenium(II) dye, [Ru(bpy)3]2+, is described. A titania sol–gel paste film was cast onto microscope slides, and the dye ion-paired to the deprotonated, hydroxylated groups on the film's surface from an aqueous solution of the dye at pH 11. The resulting sensor film is extremely oxygen sensitive, with a PO2 (S = 1/2) value (i.e. the partial pressure of oxygen required in order to reduce the original, oxygen free, luminescence intensity by 50%) of 0.011 atm. The sensor undergoes 95% response to oxygen in 4 s, and shows 95% recovery of its luminescence in argon within 7 s.

Next generation Bridge weigh-in-motion using fibre optic sensors

There have been over 3000 bridge weigh-in-motion (B-WIM) installations in 25 countries worldwide, this has led vast improvements in post processing of B-WIM systems since its introduction in the 1970’s. Existing systems are based on electrical resistance strain gauges which can be prohibitive in achieving data for long term monitoring of rural bridges due to power consumption. This paper introduces a new low-power B-WIM system using fibre optic sensors (FOS). The system consisted of a series of FOS which were attached to the soffit of an existing integral bridge with a single span of 19m. The site selection criteria and full installation process has been detailed in the paper. A method of calibration was adopted using live traffic at the bridge site and based on this calibration the accuracy of the system was determined. New methods of axle detection for B-WIM were investigated and verified in the field.

Assessment Of various sensors for structural health monitoring for bridge weigh-in-motion (B-WIM).

In recent years, Structural Health Monitoring (SHM) systems have been developed to monitor bridge deterioration, assess real load levels and hence extend bridge life and safety. A road bridge is only safe if the stresses caused by the passing vehicles are less than the capacity of the bridge to resist them. Conventional SHM systems can be used to improve knowledge of the bridges capacity to resist stresses but generally give no information on the causes of any increase in stresses (based on measuring strain). The concept of in Bridge Weigh-in-Motion (B-WIM) is to establish axle loads, without interruption to traffic flow, by using strain sensors at a bridge soffit and subsequently converting the data to real time axle loads or stresses. Recent studies have shown it would be most beneficial to develop a portable system which can be easily attached to existing and new bridge structures for a specified monitoring period. The sensors could then be left in place while the data acquisition can be moved for various other sites. Therefore it is necessary to find accurate sensors capable of capturing peak strains under dynamic load and suitable methods for attaching these strain sensors to existing and new bridge structures. Additionally, it is important to ensure accurate strain transfer between concrete and steel, the adhesives layer and the strain sensor. This paper describes research investigating the suitably of using various sensors for the monitoring of concrete structures under dynamic vehicle load. Electrical resistance strain (ERS) gauges, vibrating wire (VW) gauges and fibre optic sensors (FOS) are commonly used for SHM. A comparative study will be carried out to select a suitable sensor for a bridge Weigh in Motion System. This study will look at fixing methods, durability, scanning rate and accuracy range. Finite element modeling is used to predict the strains which are then validated in laboratory trials.

Clustering-Based Ensemble Learning for Activity Recognition in Smart Homes

Application of sensor-based technology within activity monitoring systems is becoming a popular technique within the smart environment paradigm. Nevertheless, the use of such an approach generates complex constructs of data, which subsequently requires the use of intricate activity recognition techniques to automatically infer the underlying activity. This paper explores a cluster-based ensemble method as a new solution for the purposes of activity recognition within smart environments. With this approach activities are modelled as collections of clusters built on different subsets of features. A classification process is performed by assigning a new instance to its closest cluster from each collection. Two different sensor data representations have been investigated, namely numeric and binary. Following the evaluation of the proposed methodology it has been demonstrated that the cluster-based ensemble method can be successfully applied as a viable option for activity recognition. Results following exposure to data collected from a range of activities indicated that the ensemble method had the ability to perform with accuracies of 94.2% and 97.5% for numeric and binary data, respectively. These results outperformed a range of single classifiers considered as benchmarks.

Extruded colour-based plastic film for the measurement of dissolved CO2

Dissolved CO2 measurements are usually made using a Severinghaus electrode, which is bulky and can suffer from electrical interference. In contrast, optical sensors for gaseous CO2, whilst not suffering these problems, are mainly used for making gaseous (not dissolved) CO2 measurements, due to dye leaching and protonation, especially at high ionic strengths (>0.01 M) and acidity (<pH 4). This is usually prevented by coating the sensor with a gas-permeable, but ion-impermeable, membrane (GPM). Herein, we introduce a highly sensitive, colourimetric-based, plastic film sensor for the measurement of both gaseous and dissolved CO2, in which a pH-sensitive dye, thymol blue (TB) is coated onto particles of hydrophilic silica to create a CO2-sensitive, TB-based pigment, which is then extruded into low density polyethylene (LDPE) to create a GPM-free, i.e. naked, TB plastic sensor film for gaseous and dissolved CO2 measurements. When used for making dissolved CO2 measurements, the hydrophobic nature of the LDPE renders the film: (i) indifferent to ionic strength, (ii) highly resistant to acid attack and (iii) stable when stored under ambient (dark) conditions for >8 months, with no loss of colour or function. Here, the performance of the TB plastic film is primarily assessed as a dissolved CO2 sensor in highly saline (3.5 wt%) water. The TB film is blue in the absence of CO2 and yellow in its presence, exhibiting 50% transition in its colour at ca. 0.18% CO2. This new type of CO2 sensor has great potential in the monitoring of CO2 levels in the hydrosphere, as well as elsewhere, e.g. food packaging and possibly patient monitoring.