J. Sens. Actuator Netw.2015, 4(1), 30-49; doi:10.3390/jsan4010030 - published 9 March 2015 Show/Hide Abstract
Abstract: Sub-Saharan Africa contains the highest number of people affected by droughts. Although this can easily be mitigated through the provision of timely, reliable and relevant weather forecasts, the sparse network of weather stations in most of these countries makes this difficult. Rapid development in wireless sensor networks has resulted in weatherboards capable of capturing weather parameters at the micro-level. Although these weatherboards offer a viable solution to Africa’s drought, the acceptability of such data by meteorologists is only possible if these sensors are calibrated and their field readiness scientifically evaluated. This is the contribution of this paper; we present results of a calibration exercise that was carried out to: (1) measure and correct lag, random and systematic errors; (2) determine if Perspex was an ideal material for building sensor boards’ enclosures; and (3) identify sensor boards’ battery charging and depletion rates. The result is a calibration report detailing actual error and uncertainty values for atmospheric pressure, humidity and temperature sensors, as well as the recharge and discharge curves of the batteries. The results further ruled out the use of Perspex for enclosing the sensor boards. These experiments pave the way for the design and implementation of a sensor-based weather monitoring system (SenseWeather) that was piloted in two regions in Kenya.
J. Sens. Actuator Netw.2015, 4(1), 2-29; doi:10.3390/jsan4010002 - published 4 February 2015 Show/Hide Abstract
Abstract: The automotive industry could be facing a situation of profound change and opportunity in the coming decades. There are a number of influencing factors such as increasing urban and aging populations, self-driving cars, 3D parts printing, energy innovation, and new models of transportation service delivery (Zipcar, Uber). The connected car means that vehicles are now part of the connected world, continuously Internet-connected, generating and transmitting data, which on the one hand can be helpfully integrated into applications, like real-time traffic alerts broadcast to smartwatches, but also raises security and privacy concerns. This paper explores the automotive connected world, and describes five killer QS (Quantified Self)-auto sensor applications that link quantified-self sensors (sensors that measure the personal biometrics of individuals like heart rate) and automotive sensors (sensors that measure driver and passenger biometrics or quantitative automotive performance metrics like speed and braking activity). The applications are fatigue detection, real-time assistance for parking and accidents, anger management and stress reduction, keyless authentication and digital identity verification, and DIY diagnostics. These kinds of applications help to demonstrate the benefit of connected world data streams in the automotive industry and beyond where, more fundamentally for human progress, the automation of both physical and now cognitive tasks is underway.
J. Sens. Actuator Netw.2014, 3(4), 297-330; doi:10.3390/jsan3040297 - published 5 December 2014 Show/Hide Abstract
Abstract: This paper explores the network performance and costs associated with the deployment, labor, and maintenance of a long-term outdoor multi-hop wireless sensor network (WSN) located at the Audubon Society of Western Pennsylvania (ASWP), which has been in operation for more than four years for environmental data collection. The WSN performance is studied over selected time periods during the network deployment time, based on two different TinyOS-based WSN routing protocols: commercial XMesh and the open-source Collection Tree Protocol (CTP). Empirical results show that the network performance is improved with CTP (i.e., 79% packet reception rate, 96% packet success rate and 0.2% duplicate packets), versus using XMesh (i.e., 36% packet reception rate and 46% packet success rate, with 3%–4% duplicate packets). The deployment cost of the 52-node, 253-sensor WSN is $31,500 with an additional $600 per month in labor and maintenance resulting in a cost of $184 m−2·y−1 of sensed area. Network maintenance during the first four years of operation was performed on average every 12 days, costing approximately $187 for each field visit.
J. Sens. Actuator Netw.2014, 3(4), 274-296; doi:10.3390/jsan3040274 - published 4 November 2014 Show/Hide Abstract
Abstract: Network coding techniques are usually applied upon network-layer protocols to improve throughput in wireless networks. In scenarios with multiple unicast sessions, fairness is also an important factor. Therefore, a network coding-aware packet-scheduling algorithm is required. A packet-scheduling algorithm determines which packet to send next from a node’s packet backlog. Existing protocols mostly employ a basic round-robin scheduling algorithm to give “equal” opportunities to different packet flows. In fact, this “equal”-opportunity scheduling is neither fair, nor efficient. This paper intends to accentuate the importance of a coding-aware scheduling scheme. With a good scheduling scheme, we can gain more control over the per-flow throughput and fairness. Specifically, we first formulate a static scheduling problem and propose an algorithm to find the optimal scheduling scheme. We then extend the technique to a dynamic setting and, later, to practical routing protocols. Results show that the algorithm is comparatively scalable, and it can improve the throughput gain when the network is not severely saturated. The fairness among flows is drastically improved as a result of this scheduling scheme.
J. Sens. Actuator Netw.2014, 3(4), 245-273; doi:10.3390/jsan3040245 - published 14 October 2014 Show/Hide Abstract
Abstract: In this paper, a novel concept of coupling the actuators of an automated order picking system for pouch packed goods with an embedded CCD camera sensor by means of image processing and machine learning is presented. The picking system mechanically combines the conveyance and singularization of a still-connected chain of pouch packed goods in a single machinery. The proposed algorithms perform a per-frame processing of the captured images in real-time to detect the sealed seams of the ongoing pouches. The detections are used to deduce cutting decisions in order to control the system’s actuators, namely the drive pulley for conveyance and the cutting device for the separation. Within this context, two controlling strategies are presented as well which specify the interaction of the sensor and the actuators. The detection is carried out by two different marker detection strategies: enhanced Template Matching as a heuristic and Support Vector Machines as a supervised classification based concept. Depending on the employed marker, detection rates of almost 100% with a calculation time of less than 40 ms are possible. From a logistic point of view, sealed seam widths of 20 mm prove feasible.