Processing multiple image streams for real-time monitoring of parking lots

We present a system to detect parked vehicles in a typical parking complex using multiple streams of images captured through IP connected devices. Compared to traditional object detection techniques and machine learning methods, our approach is significantly faster in detection speed in the presence of multiple image streams. It is also capable of comparable accuracy when put to test against existing methods. And this is achieved without the need to train the system that machine learning methods require. Our approach uses a combination of psychological insights obtained from human detection and an algorithm replicating the outcomes of a SVM learner but without the noise that compromises accuracy in the normal learning process. Performance enhancements are made on the algorithm so that it operates well in the context of multiple image streams. The result is faster detection with comparable accuracy. Our experiments on images captured from a local test site shows very promising results for an implementation that is not only effective and low cost but also opens doors to new parking applications when combined with other technologies.<br /

Application of double-phase liquid phase microextraction in the determination of partition coefficients and analysis of pesticides in water samples

A simple and solvent-minimized sample preparation technique based on two-phase hollow fiber-protected liquid-phase microextraction has been developed and used for the determination of partition coefficient and analysis of selected pesticides in environmental water samples. The analysis was performed by gas chromatography–electron capture detector. Three pesticides namely hexaconazole, quinalphos, and methidathion were considered as target analytes. Extraction conditions such as solvent identity, salt concentration, stirring speed, extraction time, length of the hollow fiber, and volume of donor phase were optimized. The analytes were extracted from a donor phase (water sample) through 3 µL of an organic solvent immobilized in the pores of a porous polypropylene hollow fiber and then into the acceptor phase present inside the hollow fiber. Excellent extractions of the analytes were achieved under the optimized conditions, with relative standard deviations of 4.6–7.9%, correlation coefficients (r2) of 0.9954–0.9986 and limits of detection of 3–7 ng L-1. The proposed method provided good average enrichment factors of up to 250-fold. The partition coefficients of the analytes determined were found to be directly correlated with the enrichment factor. The present methodology also confirms the robustness of microextraction for monitoring trace levels of pesticides in environmental water samples