A WIRELESS SENSOR NETWORK BOARD FOR ENVIRONMENTAL MONITORING USING GNSS AND ANALOG TRIAXIAL ACCELEROMETER

Wireless Sensor Networks (WSNs) have attracted an increasing attention in recent years because of the large number of potential applications. They are used for collecting, storing and sharing data, for monitoring applications, surveillance purposes and much more. On the other hand GNSSs are used in various systems devoted to monitor different atmospheric parameters and to trace displacements of landslides and glaciers in severe environmental conditions and in all weather situations. A first example of low cost DGPS wireless sensor network was installed in 2009 on a serac located at 4100 m above a populated area in the Aosta Valley, Italy, and it is still operative. This work presents an evolution of the WSN node used in that systems with improved functionalities and flexibility. The electronic board developed as a multipurpose board to be used in different WSNs, has been completely redesigned as an open system in order to reduce its sizes and to be configured by only varying the firmware on the microcontroller. It allows different interfaces and is equipped with a recovery system, guaranteed by a watchdog chip which continuously monitor the onboard microcontroller. The board is equipped with both a GNSS module and an analog triaxial accelerometer in order to merge GNSS raw data and accelerometer data to keep track of both fast events and slow events. A free open source operative system has been ported on the microcontroller in order to perform multiple operations and to manage the communications between the network nodes with improved efficiency. The board firmware can be modified in real time using a custom bootloader to avoid difficult maintenance operations

RFID technology applied to the glacial environment: MALATRA electronic system design and experimental data

The higher mountains of the Alps focus in the western part of Europe and favor a high concentration of glaciers in this area. The Aosta Valley region is surrounded by mountains, more than the 50% of its territory lying above 2000 m a.s.l. In the summer, most of the water supply of the region relies on the contribution given by snowmelt and, partially, by ice melt. Study of glacial processes is thus very important in this region. In this context the MALATRÀ project (led by Fondazione Montagna Sicura and Envisens Technologies) is created to develop a low-cost instrumentation capable of measuring with continuity the physical parameters of snow and ice. The instrumentation consists of a miniaturized electronic device (tag) equipped with sensors and placed inside an ovoidal small-dimension (48 mm diameter and 180 mm length) plastic capsule. Moreover, the implementation of radio frequency identification technology (RFID) allows remote communication from the surface with the tags placed deep into the glacier, thus saving time, effort and cost in collecting data. Tags allow communication at long distance working at 315 MHz frequency. At this step, the goal is to use such devices during the annual glaciological campaigns to measure the weight of the snowpack above the tag (with a pressure sensor), in order to derive the snow water equivalent (SWE) and temperature inside the ice. As a first step, the capsules will be coupled with ablation stakes installed in the ice, placed at the bottom of boreholes. Each capsule is uniquely identified by a code and can be located in a 3-D local system via radio using a localization algorithm under development. It is then, during the installation, georeferenced absolutely using a GNSS receiver. This functionality also allows for the glacier displacement measurements. Once the device has been identified, all the data stored in the internal memory can be remotely downloaded from the reader. At the current development stage the board is equipped with a precise thermometer (PT1000) and a pressure sensor to catch ice data, a magnetometer and a tri-axial accelerometer sensor to study the movement of the capsule within the ice. The performance of the system has been tested in the glacial environment with excellent results

RFID technology applied to the glacial environment: MALATRA electronic system design and experimental data

The higher mountains of the Alps focus in the western part of Europe and favor a high concentration of glaciers in this area. The Aosta Valley region is surrounded by mountains, more than the 50% of its territory lying above 2000 m a.s.l. In the summer, most of the water supply of the region relies on the contribution given by snowmelt and, partially, by ice melt. Study of glacial processes is thus very important in this region. In this context the MALATRÀ project (led by Fondazione Montagna Sicura and Envisens Technologies) is created to develop a low-cost instrumentation capable of measuring with continuity the physical parameters of snow and ice. The instrumentation consists of a miniaturized electronic device (tag) equipped with sensors and placed inside an ovoidal small-dimension (48 mm diameter and 180 mm length) plastic capsule. Moreover, the implementation of radio frequency identification technology (RFID) allows remote communication from the surface with the tags placed deep into the glacier, thus saving time, effort and cost in collecting data. Tags allow communication at long distance working at 315 MHz frequency. At this step, the goal is to use such devices during the annual glaciological campaigns to measure the weight of the snowpack above the tag (with a pressure sensor), in order to derive the snow water equivalent (SWE) and temperature inside the ice. As a first step, the capsules will be coupled with ablation stakes installed in the ice, placed at the bottom of boreholes. Each capsule is uniquely identified by a code and can be located in a 3-D local system via radio using a localization algorithm under development. It is then, during the installation, georeferenced absolutely using a GNSS receiver. This functionality also allows for the glacier displacement measurements. Once the device has been identified, all the data stored in the internal memory can be remotely downloaded from the reader. At the current development stage the board is equipped with a precise thermometer (PT1000) and a pressure sensor to catch ice data, a magnetometer and a tri-axial accelerometer sensor to study the movement of the capsule within the ice. The performance of the system has been tested in the glacial environment with excellent results

Identification of new road segments using a modified version of k-means algorithm

The present work explains how to identify transformation and new road segments in existing electronic maps by using data coming from devices carried on board on different vehicles, by using a modified version of a standard clustering algorithm called k-means. The working dataset appears as sparse clouds of points with their centres over the road segments, including other different data. Because of the spatial distribution of the points and in order to allow the algorithm to converge in a short number of steps, a simple modification has been implemented. With respect to the standard k-means algorithm which works with a fixed number of clusters, the present modified version works with a large initial number of clusters, with sizes defined a priori on the basis of the smallest possible road segment The number of clusters is progressively reduced considering, for each steps, only the clusters including a number of points above a specific thresholds. At the end of the algorithm, all the identified clusters are superimposed over a common map in order to validate if a new road segment is identified. The algorithm has been applied on different datasets acquired on the road network of Turin with good results allowing the identification of new road segments not present in the reference map and one-way roads (change in travel direction)