Chemical event tracking using a low-cost wireless chemical sensing network

A recently developed low-cost light emitting diode (LED) chemical sensing technique is integrated with a Mica2Dot wireless communications platform to form a deployable wireless chemical event indicator network. The operation of the colorimetric sensing node has been evaluated to determine its reproducibility and limit of detection for an acidic airborne contaminant. A test-scale network of five similar chemical sensing nodes is deployed in a star communication topology at fixed points within a custom built Environmental Sensing Chamber (ESC). Presented data sets collected from the deployed wireless chemical sensor network (WCSN) show that during an acidic event scenario it is possible to track the plume speed and direction, and estimate the concentration of chemical plume by examining the collective sensor data relative to individual sensor node location within the monitored environment

Enabling Broadband Data Access for the Digital Watershed with Heterogenous Wireless Networks

2008 S.C. Water Resources Conference - Addressing Water Challenges Facing the State and Regio

Towards an ultra‐low‐power low‐cost wireless visual sensor node for fine‐grain detection of forest fires

Advances in electronics, sensor technologies, embedded hardware and software are boosting the application scenarios of wireless sensor networks. Specifically, the incorporation of visual capabilities into the nodes means a milestone, and a challenge, in terms of the amount of information sensed and processed by these networks. The scarcity of resources – power, processing and memory – imposes strong restrictions on the vision hardware and algorithms suitable for implementation at the nodes. Both, hardware and algorithms must be adapted to the particular characteristics of the targeted application. This permits to achieve the required performance at lower energy and computational cost. We have followed this approach when addressing the detection of forest fires by means of wireless visual sensor networks. From the development of a smoke detection algorithm down to the design of a low‐power smart imager, every step along the way has been influenced by the objective of reducing power consumption and computational resources as much as possible. Of course, reliability and robustness against false alarms have also been crucial requirements demanded by this specific application. All in all, we summarize in this paper our experience in this topic. In addition to a prototype vision system based on a full‐custom smart imager, we also report results from a vision system based on ultra‐low‐power low‐cost commercial imagers with a resolution of 30×30 pixels. Even for this small number of pixels, we have been able to detect smoke at around 100 meters away without false alarms. For such tiny images, smoke is simply a moving grey stain within a blurry scene, but it features a particular spatio‐temporal dynamics. As described in the manuscript, the key point to succeed with so low resolution thus falls on the adequate encoding of that dynamics at algorithm levelMinisterio de Economía y Competitividad TEC2012‐38921‐C02, IPT‐2011‐1625‐430000, IPC‐ 20111009 CDTIJunta de Andalucía TIC 2338‐201

Monitoring wild animal communities with arrays of motion sensitive camera traps

Studying animal movement and distribution is of critical importance to addressing environmental challenges including invasive species, infectious diseases, climate and land-use change. Motion sensitive camera traps offer a visual sensor to record the presence of a broad range of species providing location -specific information on movement and behavior. Modern digital camera traps that record video present new analytical opportunities, but also new data management challenges. This paper describes our experience with a terrestrial animal monitoring system at Barro Colorado Island, Panama. Our camera network captured the spatio-temporal dynamics of terrestrial bird and mammal activity at the site - data relevant to immediate science questions, and long-term conservation issues. We believe that the experience gained and lessons learned during our year long deployment and testing of the camera traps as well as the developed solutions are applicable to broader sensor network applications and are valuable for the advancement of the sensor network research. We suggest that the continued development of these hardware, software, and analytical tools, in concert, offer an exciting sensor-network solution to monitoring of animal populations which could realistically scale over larger areas and time spans

Design of a WSN Platform for Long-Term Environmental Monitoring for IoT Applications

The Internet of Things (IoT) provides a virtual view, via the Internet Protocol, to a huge variety of real life objects, ranging from a car, to a teacup, to a building, to trees in a forest. Its appeal is the ubiquitous generalized access to the status and location of any "thing" we may be interested in. Wireless sensor networks (WSN) are well suited for long-term environmental data acquisition for IoT representation. This paper presents the functional design and implementation of a complete WSN platform that can be used for a range of long-term environmental monitoring IoT applications. The application requirements for low cost, high number of sensors, fast deployment, long lifetime, low maintenance, and high quality of service are considered in the specification and design of the platform and of all its components. Low-effort platform reuse is also considered starting from the specifications and at all design levels for a wide array of related monitoring application