An ultraviolet selective photodetector based on a nanocrystalline TiO2 photoelectrochemical cell

Solar ultraviolet (UV) radiation causes a range of skin disorders as well as affecting vision and the immune system. It also inhibits development of plants and animals. UV radiation monitoring is used routinely in some locations in order to alert the population to harmful solar radiation levels. There is ongoing research to develop UV-selective-sensors [1–3]. A personal, inexpensive and simple UV-selective-sensor would be desirable to measure UV intensity exposure. A prototype of such a detector has been developed and evaluated in our laboratory. It comprises a sealed two-electrode photoelectrochemical cell (PEC) based on nanocrystalline TiO2. This abundant semiconducting oxide, which is innocuous and very sta-ble, is the subject of intense study at present due to its application in dye sensitized solar cells (DSSC) [4]. Since TiO2 has a wide band gap (EG = 3.0 eV for rutile and EG = 3.2 eV for anatase), it is inher-ently UV-selective, so that UV filters are not required. This further reduces the cost of the proposed photodetector in comparison with conventional silicon detectors. The PEC is a semiconductor–electrolyte device that generates a photovoltage when it is illuminated and a corresponding photocur-rent if the external circuit is closed. The device does not require external bias, and the short circuit current is generally a linear function of illumination intensity. This greatly simplifies the elec-trical circuit needed when using the PEC as a photodetector. DSSC technology, which is based on a PEC containing nanocrystalline TiO2 sensitized with a ruthenium dye, holds out the promise of solar cells that are significantly cheaper than traditional silicon solar cells. The UV-sensor proposed in this paper relies on the cre-ation of electron–hole pairs in the TiO2 by UV radiation, so that it would be even cheaper than a DSSC since no sensitizer dye is needed. Although TiO2 has been reported as a suitable material for UV sensing [3], to the best of our knowledge, the PEC configuration described in the present paper is a new approach. In the present study, a novel double-layer TiO2 structure has been investigated. Fabrication is based on a simple and inexpensive technique for nanostructured TiO2 deposition using microwave-activated chemical bath deposition (MW-CBD) that has been reported recently [5]. The highly transparent TiO2 (anatase) films obtained are densely packed, and they adhere very well to the transparent oxide (TCO) substrate [6]. These compact layers have been studied as contacting layers in double-layer TiO2 structures for DSSC since improvement of electron extraction at the TiO2–TCO interface is expected [7]. Here we compare devices incorporating a single mesoporous nanocrystalline TiO2 structure with devices based on a double structure in which a MW-CBD film is situated between the TCO and the mesoporous nanocrystalline TiO2 layer. Besides improving electron extraction, this film could also help to block recombination of electrons transferred to the TCO with oxidized species in the electrolyte, as has been reported in the case of DSSC for compact TiO2 films obtained by other deposition tech-niques [8,9]. The two types of UV-selective sensors were characterized in detail. The current voltage characteristics, spectral response, inten-sity dependence of short circuit current and response times were measured and analyzed in order to evaluate the potential of sealed mesoporous TiO2-based photoelectrochemical cells (PEC) as low cost personal UV-photodetectors.

Selective electrochemical epinephrine sensor using self-assembled monomolecular film of 1,8,15,22-tetraaminophthalocyanatonickel(II) on gold electrode

This article describes the highly sensitive and selective determination of epinephrine (EP) using self-assembled monomolecular film (SAMF) of 1,8,15,22-tetraamino-phthalocyanatonickel(II) (4α-NiIITAPc) on Au electrode. The 4α-NiIITAPc SAMF modified electrode was prepared by spontaneous adsorption of 4α-NiIITAPc from dimethylformamide solution. The modified electrode oxidizes EP at less over potential with enhanced current response in contrast to the bare Au electrode. The standard heterogeneous rate constant (k°) for the oxidation of EP at 4α-NiIITAPc SAMF modified electrode was found to be 1.94×10−2 cm s−1 which was much higher than that at the bare Au electrode. Further, it was found that 4α-NiIITAPc SAMF modified electrode separates the voltammetric signals of ascorbic acid (AA) and EP with a peak separation of 250 mV. Using amperometric method the lowest detection limit of 50 nM of EP was achieved at SAMF modified electrode. Simultaneous amperometric determination of AA and EP was also achieved at the SAMF modified electrode. Common physiological interferents such as uric acid, glucose, urea and NaCl do not interfere within the potential window of EP oxidation. The present 4α-NiIITAPc SAMF modified electrode was also successfully applied to determine the concentration of EP in commercially available injection.

Selective combination of visual and thermal imaging for resilient localization in adverse conditions : day and night, smoke and fire

Long-term autonomy in robotics requires perception systems that are resilient to unusual but realistic conditions that will eventually occur during extended missions. For example, unmanned ground vehicles (UGVs) need to be capable of operating safely in adverse and low-visibility conditions, such as at night or in the presence of smoke. The key to a resilient UGV perception system lies in the use of multiple sensor modalities, e.g., operating at different frequencies of the electromagnetic spectrum, to compensate for the limitations of a single sensor type. In this paper, visual and infrared imaging are combined in a Visual-SLAM algorithm to achieve localization. We propose to evaluate the quality of data provided by each sensor modality prior to data combination. This evaluation is used to discard low-quality data, i.e., data most likely to induce large localization errors. In this way, perceptual failures are anticipated and mitigated. An extensive experimental evaluation is conducted on data sets collected with a UGV in a range of environments and adverse conditions, including the presence of smoke (obstructing the visual camera), fire, extreme heat (saturating the infrared camera), low-light conditions (dusk), and at night with sudden variations of artificial light. A total of 240 trajectory estimates are obtained using five different variations of data sources and data combination strategies in the localization method. In particular, the proposed approach for selective data combination is compared to methods using a single sensor type or combining both modalities without preselection. We show that the proposed framework allows for camera-based localization resilient to a large range of low-visibility conditions.

Detection of sinkhole attack in wireless sensor networks

Generally wireless sensor networks rely of many-to-one communication approach for data gathering. This approach is extremely susceptible to sinkhole attack, where an intruder attracts surrounding nodes with unfaithful routing information, and subsequently presents selective forwarding or change the data that carry through it. A sinkhole attack causes an important threat to sensor networks and it should be considered that the sensor nodes are mostly spread out in open areas and of weak computation and battery power. In order to detect the intruder in a sinkhole attack this paper suggests an algorithm which firstly finds a group of suspected nodes by analyzing the consistency of data. Then, the intruder is recognized efficiently in the group by checking the network flow information. The proposed algorithm's performance has been evaluated by using numerical analysis and simulations. Therefore, accuracy and efficiency of algorithm would be verified.

Highly sensitive electrochemical sensor for nitric oxide using the self-assembled monolayer of 1,8,15,22-tetraaminophthalo-cyanatocobalt(II) on glassy carbon electrode

Glassy carbon (GC) electrode modified with a self-assembled monolayer (SAM) of 1,8,15,22-tetraaminophthalocyanatocobalt(II) (4α-CoIITAPc) was used for the selective and highly sensitive determination of nitric oxide (NO). The SAM of 4α-CoIITAPc was formed on GC electrode by spontaneous adsorption from DMF containing 1 mM 4α-CoIITAPc. The SAM showed two pairs of well-defined redox peaks corresponding to CoIII/CoII and CoIIIPc−1/CoIIIPc−2 in 0.2 M phosphate buffer (PB) solution (pH 2.5). The SAM modified electrode showed excellent electrocatalytic activity towards the oxidation of nitric oxide (NO) by enhancing its oxidation current with 310 mV less positive potential shift when compared to bare GC electrode. In amperometric measurements, the current response for NO oxidation was linearly increased in the concentration range of 3×10−9 to 30×10−9 M with a detection limit of 1.4×10−10 M (S/N=3). The proposed method showed a better recovery for NO in human blood serum samples.

Electrochemical current rectification – a novel signal amplification strategy for highly sensitive and selective aptamer-based biosensor

Electrochemical aptamer-based (E-AB) sensors represent an emerging class of recently developed sensors. However, numerous of these sensors are limited by a low surface density of electrode-bound redox-oligonucleotides which are used as probe. Here we propose to use the concept of electrochemical current rectification (ECR) for the enhancement of the redox signal of E-AB sensors. Commonly, the probe-DNA performs a change in conformation during target binding and enables a nonrecurring charge transfer between redox-tag and electrode. In our system, the redox-tag of the probe-DNA is continuously replenished by solution-phase redox molecules. A unidirectional electron transfer from electrode via surface-linked redox-tag to the solution-phase redox molecules arises that efficiently amplifies the current response. Using this robust and straight-forward strategy, the developed sensor showed a substantial signal amplification and consequently improved sensitivity with a calculated detection limit of 114 nM for ATP, which was improved by one order of magnitude compared with the amplification-free detection and superior to other previous detection results using enzymes or nanomaterials-based signal amplification. To the best of our knowledge, this is the first demonstration of an aptamer-based electrochemical biosensor involving electrochemical rectification, which can be presumably transferred to other biomedical sensor systems.

Urban citizenship in a sensor rich society

Urban public spaces are sutured with a range of surveillance and sensor technologies that claim to enable new forms of ‘data based citizen participation’, but also increase the tendency for ‘function-creep’, whereby vast amounts of data are gathered, stored and analysed in a broad application of urban surveillance. This kind of monitoring and capacity for surveillance connects with attempts by civic authorities to regulate, restrict, rebrand and reframe urban public spaces. A direct consequence of the increasingly security driven, policed, privatised and surveilled nature of public space is the exclusion or ‘unfavourable inclusion’ of those considered flawed and unwelcome in the ‘spectacular’ consumption spaces of many major urban centres. In the name of urban regeneration, programs of securitisation, ‘gentrification’ and ‘creative’ and ‘smart’ city initiatives refashion public space as sites of selective inclusion and exclusion. In this context of monitoring and control procedures, in particular, children and young people’s use of space in parks, neighbourhoods, shopping malls and streets is often viewed as a threat to the social order, requiring various forms of remedial action. This paper suggests that cities, places and spaces and those who seek to use them, can be resilient in working to maintain and extend democratic freedoms and processes enshrined in Marshall’s concept of citizenship, calling sensor and surveillance systems to account. Such accountability could better inform the implementation of public policy around the design, build and governance of public space and also understandings of urban citizenship in the sensor saturated urban environment.

Molecular recognition of 2,4,6-trinitrotoluene by 6-aminohexanethiol and surface-enhanced Raman scattering sensor

2,4,6-trinitrotoluene (TNT) is one of the most commonly used nitro aromatic explosives in landmine, military and mining industry. This article demonstrates rapid and selective identification of TNT by surface-enhanced Raman spectroscopy (SERS) using 6-aminohexanethiol (AHT) as a new recognition molecule. First, Meisenheimer complex formation between AHT and TNT is confirmed by the development of pink colour and appearance of new band around 500 nm in UV-visible spectrum. Solution Raman spectroscopy study also supported the AHT:TNT complex formation by demonstrating changes in the vibrational stretching of AHT molecule between 2800-3000 cm−1. For surface enhanced Raman spectroscopy analysis, a self-assembled monolayer (SAM) of AHT is formed over the gold nanostructure (AuNS) SERS substrate in order to selectively capture TNT onto the surface. Electrochemical desorption and X-ray photoelectron studies are performed over AHT SAM modified surface to examine the presence of free amine groups with appropriate orientation for complex formation. Further, AHT and butanethiol (BT) mixed monolayer system is explored to improve the AHT:TNT complex formation efficiency. Using a 9:1 AHT:BT mixed monolayer, a very low detection limit (LOD) of 100 fM TNT was realized. The new method delivers high selectivity towards TNT over 2,4 DNT and picric acid. Finally, real sample analysis is demonstrated by the extraction and SERS detection of 302 pM of TNT from spiked.

A forward and backward secure key management in wireless sensor networks for PCS/SCADA

Process Control Systems (PCSs) or Supervisory Control and Data Acquisition (SCADA) systems have recently been added to the already wide collection of wireless sensor networks applications. The PCS/SCADA environment is somewhat more amenable to the use of heavy cryptographic mechanisms such as public key cryptography than other sensor application environments. The sensor nodes in the environment, however, are still open to devastating attacks such as node capture, which makes designing a secure key management challenging. In this paper, a key management scheme is proposed to defeat node capture attack by offering both forward and backward secrecies. Our scheme overcomes the pitfalls which Nilsson et al.'s scheme suffers from, and is not more expensive than their scheme.

Fusion of in-vehicle sensor data to develop Intelligent Driver Training System (IDTS)

The over represented number of novice drivers involved in crashes is alarming. Driver training is one of the interventions aimed at mitigating the number of crashes that involve young drivers. To our knowledge, Advanced Driver Assistance Systems (ADAS) have never been comprehensively used in designing an intelligent driver training system. Currently, there is a need to develop and evaluate ADAS that could assess driving competencies. The aim is to develop an unsupervised system called Intelligent Driver Training System (IDTS) that analyzes crash risks in a given driving situation. In order to design a comprehensive IDTS, data is collected from the Driver, Vehicle and Environment (DVE), synchronized and analyzed. The first implementation phase of this intelligent driver training system deals with synchronizing multiple variables acquired from DVE. RTMaps is used to collect and synchronize data like GPS, vehicle dynamics and driver head movement. After the data synchronization, maneuvers are segmented out as right turn, left turn and overtake. Each maneuver is composed of several individual tasks that are necessary to be performed in a sequential manner. This paper focuses on turn maneuvers. Some of the tasks required in the analysis of ‘turn’ maneuver are: detect the start and end of the turn, detect the indicator status change, check if the indicator was turned on within a safe distance and check the lane keeping during the turn maneuver. This paper proposes a fusion and analysis of heterogeneous data, mainly involved in driving, to determine the risk factor of particular maneuvers within the drive. It also explains the segmentation and risk analysis of the turn maneuver in a drive.

Towards continuous surveillance of fruit flies using sensor networks and machine vision

In Australia, the Queensland fruit fly (B. tryoni), is the most destructive insect pest of horticulture, attacking nearly all fruit and vegetable crops. This project has researched and prototyped a system for monitoring fruit flies so that authorities can be alerted when a fly enters a crop in a more efficient manner than is currently used. This paper presents the idea of our sensor platform design as well as the fruit fly detection and recognition algorithm by using machine vision techniques. Our experiments showed that the designed trap and sensor platform is capable to capture quality fly images, the invasive flies can be successfully detected and the average precision of the Queensland fruit fly recognition is 80% from our experiment.

Robot navigation in sensor space

This thesis investigates the problem of robot navigation using only landmark bearings. The proposed system allows a robot to move to a ground target location specified by the sensor values observed at this ground target posi- tion. The control actions are computed based on the difference between the current landmark bearings and the target landmark bearings. No Cartesian coordinates with respect to the ground are computed by the control system. The robot navigates using solely information from the bearing sensor space. Most existing robot navigation systems require a ground frame (2D Cartesian coordinate system) in order to navigate from a ground point A to a ground point B. The commonly used sensors such as laser range scanner, sonar, infrared, and vision do not directly provide the 2D ground coordi- nates of the robot. The existing systems use the sensor measurements to localise the robot with respect to a map, a set of 2D coordinates of the objects of interest. It is more natural to navigate between the points in the sensor space corresponding to A and B without requiring the Cartesian map and the localisation process. Research on animals has revealed how insects are able to exploit very limited computational and memory resources to successfully navigate to a desired destination without computing Cartesian positions. For example, a honeybee balances the left and right optical flows to navigate in a nar- row corridor. Unlike many other ants, Cataglyphis bicolor does not secrete pheromone trails in order to find its way home but instead uses the sun as a compass to keep track of its home direction vector. The home vector can be inaccurate, so the ant also uses landmark recognition. More precisely, it takes snapshots and compass headings of some landmarks. To return home, the ant tries to line up the landmarks exactly as they were before it started wandering. This thesis introduces a navigation method based on reflex actions in sensor space. The sensor vector is made of the bearings of some landmarks, and the reflex action is a gradient descent with respect to the distance in sensor space between the current sensor vector and the target sensor vec- tor. Our theoretical analysis shows that except for some fully characterized pathological cases, any point is reachable from any other point by reflex action in the bearing sensor space provided the environment contains three landmarks and is free of obstacles. The trajectories of a robot using reflex navigation, like other image- based visual control strategies, do not correspond necessarily to the shortest paths on the ground, because the sensor error is minimized, not the moving distance on the ground. However, we show that the use of a sequence of waypoints in sensor space can address this problem. In order to identify relevant waypoints, we train a Self Organising Map (SOM) from a set of observations uniformly distributed with respect to the ground. This SOM provides a sense of location to the robot, and allows a form of path planning in sensor space. The navigation proposed system is analysed theoretically, and evaluated both in simulation and with experiments on a real robot.