Wireless aquatic navigator for detection and analysis (WANDA)

The cost of monitoring and detecting pollutants in natural waters is of major concern. Current and forthcoming bodies of legislation will continue to drive demand for spatial and selective monitoring of our environment, as the focus increasingly moves towards effective enforcement of legislation through detection of events, and unambiguous identification of perpetrators. However, these monitoring demands are not being met due to the infrastructure and maintenance costs of conventional sensing models. Advanced autonomous platforms capable of performing complex analytical measurements at remote locations still require individual power, wireless communication, processor and electronic transducer units, along with regular maintenance visits. Hence the cost base for these systems is prohibitively high, and the spatial density and frequency of measurements are insufficient to meet requirements. In this paper we present a more cost effective approach for water quality monitoring using a low cost mobile sensing/communications platform together with very low cost stand-alone ‘satellite’ indicator stations that have an integrated colorimetric sensing material. The mobile platform is equipped with a wireless video camera that is used to interrogate each station to harvest information about the water quality. In simulation experiments, the first cycle of measurements is carried out to identify a ‘normal’ condition followed by a second cycle during which the platform successfully detected and communicated the presence of a chemical contaminant that had been localised at one of the satellite stations

Exploration of Miniature Flexible Devices Empowered by Van Der Waals Material

This research mainly focuses on the fabrication of miniature flexible devices empowered by van der Waals materials. Through the extensive experiments contained in this thesis, by exploring the characteristics of van der Waals materials, optimizing the manufacturing process of lithography technology, and characterizing the photoelectric performance of micro devices, this thesis has promoted the development of micro flexible device manufacturing and expanded its applications in the fields of biological detection, medical treatment, and environmental monitoring. We introduced a miniature van der Waals semiconductor empowered vertical color sensor, which saves three times the volume space compared to the traditional planer color sensor and includes multiple optical aberration correction functions as well. Such a small red, green, and blue (RGB) color sensor can be applied in bionic eyes, breaking through the limitations of existing black and white recognition. On this basis, we further explored the stretchability of two-dimensional materials represented by MoS2. We proposed a chemical treatment method combined with gold nanoparticles and (3-mercaptopropyl)trimethoxysilane (MPTMS) to realize the relocation of flexible micro devices. This method improves the adhesion between the material layer and the flexible substrate (PDMS), which significantly increases the flexible device stretchability, and prolongs its service life. Through the above work, this thesis explores the van der Waals materials’ properties, and optimizes the manufacturing process of micro devices, further exerts the advantages of material flexibility, therefore provides more possibilities for the development of smart wearable devices, biomedical detection, and other fields

On the Use of Low-Cost RGB-D Sensors for Autonomous Pothole Detection with Spatial Fuzzy <em>c</em>-Means Segmentation

The automated detection of pavement distress from remote sensing imagery is a promising but challenging task due to the complex structure of pavement surfaces, in addition to the intensity of non-uniformity, and the presence of artifacts and noise. Even though imaging and sensing systems such as high-resolution RGB cameras, stereovision imaging, LiDAR and terrestrial laser scanning can now be combined to collect pavement condition data, the data obtained by these sensors are expensive and require specially equipped vehicles and processing. This hinders the utilization of the potential efficiency and effectiveness of such sensor systems. This chapter presents the potentials of the use of the Kinect v2.0 RGB-D sensor, as a low-cost approach for the efficient and accurate pothole detection on asphalt pavements. By using spatial fuzzy c-means (SFCM) clustering, so as to incorporate the pothole neighborhood spatial information into the membership function for clustering, the RGB data are segmented into pothole and non-pothole objects. The results demonstrate the advantage of complementary processing of low-cost multisensor data, through channeling data streams and linking data processing according to the merits of the individual sensors, for autonomous cost-effective assessment of road-surface conditions using remote sensing technology

Signals in the Soil: Subsurface Sensing

In this chapter, novel subsurface soil sensing approaches are presented for monitoring and real-time decision support system applications. The methods, materials, and operational feasibility aspects of soil sensors are explored. The soil sensing techniques covered in this chapter include aerial sensing, in-situ, proximal sensing, and remote sensing. The underlying mechanism used for sensing is also examined as well. The sensor selection and calibration techniques are described in detail. The chapter concludes with discussion of soil sensing challenges