Multi-sensor geodetic observations for drought characterization in the Northeast Atlantic Eastern Hydrographic Region, Brazil

The lowest water availability area in Brazil is the Northeast Atlantic Eastern Hydrographic Region (NAERH). It plays a fundamental role in the lives of 24.1 million inhabitants spread throughout 874 cities. Drought is recurrent in this semiarid climate, affecting agriculture, biodiversity, the ecosystem and other environmental spheres. Therefore, the goal of this research is to combine different drought indexes to quantify drought intensity and duration in the NAERH. Besides the traditionally used rainfall data, multi-temporal data from the Gravity Recovery and Climate Experiment (GRACE) and Global Positioning System (GPS) were also used. The indexes are the Combined Climatic Deviation Index (CCDI), Drought Severity Index (DSI) and Vertical Crustal Deformation Index (DI_VCD). The Standardized Precipitation Index (SPI) was used for validation of the other indexes through the Spearman rank correlation, which retrieved ρ = 0.76 and 0.68 between the CCDI and the SPI-03/06. On the other hand, DSI correlated with the SPI-24/36 with ρ = 0.67/0.75. Despite limitations, the DI_VCD accurately detected the frequencies of hydrological droughts. All indexes identified the last severe drought from 2012 to 2018, and its persistence throughout 2019 and 2020. The combined indexes approach reveals nuances of the indexes, improving the baseline to thoroughly understand drought at different temporal scales.

Low-Cost and Data Anonymised City Traffic Flow Data Collection to Support Intelligent Traffic System

There are many methods of collecting traffic flow data, especially using smart phone apps. However, few current solutions balance the need for collecting full route data whilst respecting privacy and remaining low-cost. This project looks into the creation of a wireless sensor network (WSN) that can balance these requirements in an attempt to negate some of the concerns that come with this type of technology. Our proposed system only collects location data within a defined city area. This data is collected with a randomized identifier, which limits repeated identification of the source vehicle and its occupants. Data collected is shared between vehicle and roadside base stations when the two are in range. To deal with the fluid nature of this scenario, a purposely designed Media Access Control (MAC) protocol was designed and implemented using the beacon-slotted ALOHA (Advocates of Linux Open-source Hawaii Association) mechanism.

Design and testing of a multi-sensor pedestrian location and navigation platform

Navigation and location technologies are continually advancing, allowing ever higher accuracies and operation under ever more challenging conditions. The development of such technologies requires the rapid evaluation of a large number of sensors and related utilization strategies. The integration of Global Navigation Satellite Systems (GNSSs) such as the Global Positioning System (GPS) with accelerometers, gyros, barometers, magnetometers and other sensors is allowing for novel applications, but is hindered by the difficulties to test and compare integrated solutions using multiple sensor sets. In order to achieve compatibility and flexibility in terms of multiple sensors, an advanced adaptable platform is required. This paper describes the design and testing of the NavCube, a multi-sensor navigation, location and timing platform. The system provides a research tool for pedestrian navigation, location and body motion analysis in an unobtrusive form factor that enables in situ data collections with minimal gait and posture impact. Testing and examples of applications of the NavCube are provided.