Low-cost Sensor Platform Research Articles

(Invited) Industrialization Trial of a Biosensor Technology

A biosensing system is commercialized based on a concept of physiological balance for healthcare. The addition of low-cost biochemical sensors to the sensing system would help with scientific prescriptions based on contemporary medicine. As a candidate for a low-cost and robust chemical sensor platform, the ion-sensitive field-effect transistor (ISFET) has long been examined. After reviewing past ISFET research, our two approaches for new business trials are discussed. One approach is based on the progressiveness of technology that relies on a public finance with existing big companies. Another approach is a lean startup based on a customer development model for entrepreneurs.

Can commercial low-cost sensor platforms contribute to air quality monitoring and exposure estimates?

The emergence of low-cost, user-friendly and very compact air pollution platforms enable observations at high spatial resolution in near-real-time and provide new opportunities to simultaneously enhance existing monitoring systems, as well as engage citizens in active environmental monitoring. This provides a whole new set of capabilities in the assessment of human exposure to air pollution. However, the data generated by these platforms are often of questionable quality.We have conducted an exhaustive evaluation of 24 identical units of a commercial low-cost sensor platform against CEN (European Standardization Organization) reference analyzers, evaluating their measurement capability over time and a range of environmental conditions. Our results show that their performance varies spatially and temporally, as it depends on the atmospheric composition and the meteorological conditions. Our results show that the performance varies from unit to unit, which makes it necessary to examine the data quality of each node before its use.In general, guidance is lacking on how to test such sensor nodes and ensure adequate performance prior to marketing these platforms. We have implemented and tested diverse metrics in order to assess if the sensor can be employed for applications that require high accuracy (i.e., to meet the Data Quality Objectives defined in air quality legislation, epidemiological studies) or lower accuracy (i.e., to represent the pollution level on a coarse scale, for purposes such as awareness raising).Data quality is a pertinent concern, especially in citizen science applications, where citizens are collecting and interpreting the data. In general, while low-cost platforms present low accuracy for regulatory or health purposes they can provide relative and aggregated information about the observed air quality.

Micro/Miniature Aerial Vehicle Guidance for Hurricane Research

We present an investigation of the Lagrangian dynamics of a hurricane from the perspective of using micro aerial vehicles (MAVs) or small unmanned aircraft systems as mobile sensors for hurricane research and monitoring. The low cost of MAVs allows the use of more sensors for volumetric in situ measurements, particularly in high-risk locations where larger more expensive systems cannot be used. However, the limited flight speed of MAVs enforces severe restrictions on potential flight plans. In the face of 70-m/s horizontal winds, a MAV with only 10-m/s flight capability has very little directional control. Fortunately, vertical wind speeds in the hurricane are much lower and have limited spatial extent. Using Lagrangian coherent structure techniques and simplified vehicle simulations, we develop an understanding of the transport dynamics of a simulated hurricane and apply this understanding to a high-level control scheme to enable MAV navigation and guidance near the hurricane. By smartly adjusting their altitude, simulated MAVs are able to navigate into the hurricane eye at a very high success rate. Our findings suggest that the smart use of the existing background flow could allow the use of low-cost sensor platforms in extreme environments.

Surface plasmon resonance sensor based on molecularly imprinted polymer film for detection of histamine

The demand for advanced, sensitive, and low-cost sensor platforms is growing. However, sensors containing biological recognition elements sometimes present restrictions, which limit their use. This work focused on the development of surface plasmon resonance (SPR) based on a molecularly imprinted polymer (MIP) film, which builds a foundation for biomimetic sensors. The MIP films in the sensor chip were prepared by spin-coating method. The MIP film was found to be readily incorporated into the sensor for detection of histamine in aqueous media. The effect of pH conditions was also investigated. The sensing technique allows for the detection of histamine in a wide range of concentration from 25μgL−1 to 1000μgL−1. By using structural analogs, the sensor platform was demonstrated to be specific for the detection of histamine.

Pencil-trace on printed silver interdigitated electrodes for paper-based NO2 gas sensors

The pencil-drawn sensor is expected to enable a simple, low-cost, and reproducible paper-based sensor platform for widely deployed wireless environmental monitoring of NO2. Herein, we demonstrated a rapid prototyping of chemiresistor-type NO2 sensor by mechanical abrasion of an 8B pencil to form a stripe of uniform graphitic coating on printed silver interdigitated electrodes (IDEs). The Ag IDEs not only offer a low resistance but also provide the assembly of Ag nanoparticles into exfoliated graphene sheets for the paper-based NO2 gas sensors in order to realise much higher sensitivity and better reproducibility comparing with pencil-drawn sensors directly on weighing paper.

Real-Time Monitoring of Aptamer Functionalization and Detection of Ara H1 by Electrochemical Impedance Spectroscopy and Dissipation-Mode Quartz Crystal Microbalance

Peanut allergy, the most common cause of fatal-food-related anaphylaxis, is a lifelong disorder and the only existing therapy is avoidance of allergen-containing food. Detection of Ara h 1, the most important peanut allergen, is commonly performed by immunoassay techniques relying on the use of expensive and relatively unstable antibodies. Aptamers can overcome these drawbacks and offer a great potential for the development of reliable biosensors. Therefore, we will present a novel aptamer-based sensor for the label-free detection of Ara h 1. Amino (NH2)-terminated Ara h 1 aptamers were covalently attached to carboxylated gold surfaces employing carbodiimide chemistry. This functionalization procedure was followed in real time by electrochemical impedance spectroscopy and quartz crystal microbalance with dissipation monitoring. Subsequently, the functionalized surfaces were exposed to Ara h 1 solutions in TGK buffer. By combining the two techniques, we can measure in a wide concentration regime varying from the low nanomolar range (1-15 nM) via electrochemical impedance spectroscopy to the higher concentrations (25-250 nM) by microgravimetric detection. In summary, a fast, low-cost and sensitive sensor platform for Ara h 1 detection has been developed, which can be operated as a ‘stand-alone device’, making it well suited for applications such as the screening of trace allergens.

Mobile Relay Configuration in Data-Intensive Wireless Sensor Networks

Wireless Sensor Networks (WSNs) are increasingly used in data-intensive applications such as microclimate monitoring, precision agriculture, and audio/video surveillance. A key challenge faced by data-intensive WSNs is to transmit all the data generated within an application's lifetime to the base station despite the fact that sensor nodes have limited power supplies. We propose using low-cost disposable mobile relays to reduce the energy consumption of data-intensive WSNs. Our approach differs from previous work in two main aspects. First, it does not require complex motion planning of mobile nodes, so it can be implemented on a number of low-cost mobile sensor platforms. Second, we integrate the energy consumption due to both mobility and wireless transmissions into a holistic optimization framework. Our framework consists of three main algorithms. The first algorithm computes an optimal routing tree assuming no nodes can move. The second algorithm improves the topology of the routing tree by greedily adding new nodes exploiting mobility of the newly added nodes. The third algorithm improves the routing tree by relocating its nodes without changing its topology. This iterative algorithm converges on the optimal position for each node given the constraint that the routing tree topology does not change. We present efficient distributed implementations for each algorithm that require only limited, localized synchronization. Because we do not necessarily compute an optimal topology, our final routing tree is not necessarily optimal. However, our simulation results show that our algorithms significantly outperform the best existing solutions.