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A miniaturised silicon biosensor system for the detection of triglycerides and urea

Biosensors bring together the strengths of biochemical interactions combined with electronic detection and can be used for medical diagnostics, environmental analysis, food quality control, drug detection, etc. Silicon based sensors have the advantages of being compact and thus requiring small sample quantity for testing, ease in signal processing and possibility of circuit integration and also lower costs if made by batch processing. Electrolyte–Insulator-Semiconductor capacitors (EISCAP) show a shift in the measured capacitance voltage (CV) characteristic with changes in the pH of the electrolyte. Many biological reactions, especially enzyme mediated ones, involve changes in the pH of the electrolyte and an EISCAP can be effectively used for the detection of biological compounds. (...more details)


Advanced sensing technologies for superconducting devices test at CERN

Realizing and tuning the largest machine ever built by the human kind, the Large Hadron Collider (LHC) at CERN, fostered a powerful challenge in advanced sensing technologies. As a matter of fact, LHC is the coldest massive site of the universe, with a vacuum level lower than free space (one tenth than the moon surface) and a temperature minor than the universe average. This target has been achieved by measuring several physical quantities in unexplored ranges, but above all by unprecedented precision. (...more details)


Edge Mining: Making sense of sensor data

In this talk, I will look at the concept of edge mining --- data mining that takes place at the edge of a wireless sensor network. Initially, we want our sensor networks to be as flexible as possible but as the area matures, automating information extracting into continuous analytics and pushing such analytics to the edge or leaf nodes of a network can reduce the infrastructural cost of the sensor network and thus enable many applications that would otherwise be infeasible. The talk will be rooted in my experience with deploying wireless sensor nets and deriving meaningful information from the resultant data streams. (...more details)


Feature selection for pattern analysis and mining of sensors’ data

The data collected by different sensors need to be analyzed for various recognition problems, such as human activity recognition from wearable sensors, odor recognition from chemical sensors (E-nose) or detection of explosives from calorimetric sensor array. Feature selection is an important step towards dimensionality reduction of high dimensional data and facilitates further analysis by selecting important information while discarding unwanted or redundant information. Feature subset selection techniques also help in finding good sensor subsets and can be applied to optimize sensor locations in wireless sensor networks. In this talk, I will discuss soft computing based approaches for feature subset selection and present some proposed algorithms useful for pattern recognition or mining of real life sensors’ data with simulation experiments and results. (...more details)


Imaging Dielectric Structure Using Transmission Line Waveguides

Many sensing applications use imaging of target materials to map specific parameters of interest. Most often such imaging employs electromagnetic radiation over a wavelength regime chosen to the highlight the physical properties sought. In this talk, a recently developed form of imaging using the electromagnetic field generated by a guided pulse propagating along a pair of transmission lines will be presented. The interaction of the incident electric field with the polarisable material of the sample can be used to map its composition, particularly its water distribution since water has a high permittivity compared to most other naturally occurring materials. Examples where this technique has been used to determine the structural properties of timber and the integrity of road sub course material will be given along with emerging applications in areas where other forms imaging are not feasible. (...more details)


Proposal of a sub-cent RFID using metal-patch - Problems and ways to overcome them

RFID tags are used everywhere, from passports to prepaid cards to inventories. In this talk, first the various uses of RFID tags will be discussed in brief, pointing out the key-technologies and their respective pros and cons. The main reasons hindering the wide spread deployment of passive RFID tags are high cost and limited range. The present talk will focus on developing a sub-cent RFID capable of operating from a reasonable distance, though with some compromise on the information content. The resonance behavior of backscatter from a metal patch on a metallic ground plane, separated by a dielectric, could be used as an information storing tag. The dimensions of such a tag define the poles and zeros shaping the scattered signal. By analyzing the scattered signal, the resonating frequency could be assessed. In this talk, we will discuss the possibility of using such a passive tag as a information storing device and the problems of correctly retrieving the information. The limitation of the information content could be addressed using multiple patches, either stacked on top of each other, or located transversely. Since there are ample applications of read-only RFID with limited information content, the present technology is expected to fill a substantial part of the niche of sub-cent tags. (...more details)