Wireless Sensor Network Application for Environmental Impact Analysis and Control

Traditional Wireless Sensor Networks (WSNs) applications take advantage of the new low cost low power consuming integrated sensors that appear with the evolution of Micro Electromechanical Systems (MEMS). This kind of sensors is suitable for WSNs, due to the reduced size, their interfaces and their low power consumption. However, during the last years, WSNs have found new niches of application where such sensors are not usable, due to the nature of the parameter to be measured. In these scenarios, new approaches must be taken in order to satisfy the requirements. But new problems appear, like cost and size increase. In this paper, an application where parameters like gas concentration, conductivity or pH have to be measured in a coffee factory is presented. The drawbacks of such a solution are highlighted, and the solution in the field of the wireless sensor networks adopted is detailed

Enhanced collision avoidance mechanisms for wireless sensor networks through high accuracy collision modeling

Wireless channel and multi-hop communications cause a significant number of packet collisions in Wireless Sensor Networks (WSNs). Although a collision may cause packet loss and reduce network performance, low-power wireless transceivers allow packet reception in the presence of collisions if at least one signal can provide a sufficiently high power compared with other signals. Therefore, with respect to the large number of nodes used in WSNs, which necessitates the use of simulation for protocol development, collisions should be addressed at two layers: First, collisions should be modeled at the physical layer through a high-accuracy packet reception algorithm that decides about packet reception in the presence of collisions. Second, collision avoidance mechanisms should be employed at the Medium Access Control (MAC) layer to reduce packet losses caused by collisions. Unfortunately, the existing packet reception algorithms exhibit low accuracy and impede the development of efficient collision avoidance mechanisms. From the collision avoidance perspective, existing contention-based MAC protocols do not provide reliable packet broadcasting, thereby affecting the initialization performance of WSNs. In addition, despite the benefits of schedule-based MAC protocols during the data-gathering phase, the existing mechanisms rely on unrealistic assumptions. The first major contribution of this work is CApture Modeling Algorithm (CAMA), which enables collision modeling with high accuracy and efficiency at the physical layer. The higher accuracy of CAMA against existing approaches is validated through extensive comparisons with empirical experiments. The second major contribution includes mechanisms that improve the reliability of packet broadcasting. In particular, adaptive contention window adjustment mechanisms and the Geowindow algorithm are proposed for collision avoidance during the initialization phases. These mechanisms considerably improve the accuracy of the initialization phases, without violating duration and energy efficiency requirements. As the third major contribution, a distributed and concurrent link-scheduling algorithm (called DICSA) is proposed for collision avoidance during the data-gathering phase. DICSA provides faster slot assignment, higher spatial reuse and lower energy consumption, compared with existing algorithms. Furthermore, evaluating DICSA within a MAC protocol confirms its higher throughput, higher delivery ratio, and lower end-to-end delay

New mobile positioning techniques for LOS/NLOS environments and investigation of topology influence

The advent of wireless location technology and the increase in location-based services, has meant the need to investigate efficient network-based location methods becoming of paramount importance. Therefore, the interest in wireless positioning techniques has been increasing over recent decades. Among mobile positioning techniques, the Time of Arrival (TOA) and Time Difference of Arrival (TDOA) look promising. For the purpose of dealing with such technologies, some classic algorithms such as least square, most likelihood and Taylor method have been used to solve the estimation, which distinguishes the location. However, in real practice, there are certain factors that influence the level of location accuracy. The two most significant factors are cellular topologies and non-line-of-sight (NLOS) effect. This thesis reviews existing approaches and suggests innovative methods for both line-of-sight (LOS) and NLOS scenarios. A simulation platform is designed to test and compare the performances of these algorithms. The results of the simulation compared with actual position measurements demonstrate that the innovative approaches have high positioning accuracy. Additionally, this thesis demonstrates different types of cellular topologies and develops a simulation to show how the cellular topology affects the positioning quality level. Finally, this thesis implements an experiment to exhibit how the innovative algorithms perform in the real world

Combining Cloud and sensors in a smart city environment

International audienceIn the current worldwide ICT scenario, a constantly growing number of ever more powerful devices (smartphones, sensors, household appliances, RFID devices, etc.) join the Internet, significantly impacting the global traffic volume (data sharing, voice, multimedia, etc.) and foreshadowing a world of (more or less) smart devices, or "things" in the Internet of Things (IoT) perspective. Heterogeneous resources can be aggregated and abstracted according to tailored thing-like semantics, thus enabling Things as a Service paradigm, or better a "Cloud of Things". In the Future Internet initiatives, sensor networks will assume even more of a crucial role, especially for making smarter cities. Smarter sensors will be the peripheral elements of a complex future ICT world. However, due to differences in the "appliances" being sensed, smart sensors are very heterogeneous in terms of communication technologies, sensing features and elaboration capabilities. This article intends to contribute to the design of a pervasive infrastructure where new generation services interact with the surrounding environment, thus creating new opportunities for contextualization and geo-awareness. The architecture proposal is based on Sensor Web Enablement standard specifications and makes use of the Contiki Operating System for accomplishing the IoT. Smart cities are assumed as the reference scenario

Footprint Modeling and Connectivity Analysis for Wireless Sensor Networks

A wireless sensor network is a network consisting of spatially distributed, sometimeautonomous sensors, communicating wirelessly to cooperatively achieve some task. For example, a wireless sensor network may be used for habitat monitoring to ascertain the environment’s temperature, pressure, humidity, etc. In order for a wireless sensor network to provide such data, one needs to ensure there is connectivity between nodes. That is, nodes can communicate to exchange information. To analyze connectivity between sensors, the radio communication range of each sensor, also called the communication footprint, needs to be known. To date, the models used to analyze a sensor’s radio communication footprint have been overly simplistic (i.e., isotropic) and thus yield results not found in practice. Footprints are highly dependent on the deployment environments, which are typically heterogeneous and non-isotropic in structure. In this work, a ‘weak-monotonicity’ (W-M) model is leveraged to represent a footprint’s non-isotropic behavior. The work also considers the heterogeneity of the environment through the use of the log-normal shadowing model. In particular, the usable percentage of the W-M footprint (the area where the power exceeds the receiver threshold) in such environments is considered through analysis and simulation. We then develop an enhanced footprint model which overlays multiple W-M patterns and use this method to represent experimental propagation data. The work also considers the use of graph theory methods to analyze the connectivity of randomly deployed networks in nonhomogeneous, non-isotropic environments

FPGA-Based Wireless Sensor Node Architecture for High Performance Applications

While for years traditional wireless sensor nodes have been based on ultra-low power microcontrollers with sufficient but limited computing power, the complexity and number of tasks of today’s applications are constantly increasing. Increasing the node duty cycle is not feasible in all cases, so in many cases more computing power is required. This extra computing power may be achieved by either more powerful microcontrollers, though more power consumption or, in general, any solution capable of accelerating task execution. At this point, the use of hardware based, and in particular FPGA solutions, might appear as a candidate technology, since though power use is higher compared with lower power devices, execution time is reduced, so energy could be reduced overall. In order to demonstrate this, an innovative WSN node architecture is proposed. This architecture is based on a high performance high capacity state-of-the-art FPGA, which combines the advantages of the intrinsic acceleration provided by the parallelism of hardware devices, the use of partial reconfiguration capabilities, as well as a careful power-aware management system, to show that energy savings for certain higher-end applications can be achieved. Finally, comprehensive tests have been done to validate the platform in terms of performance and power consumption, to proof that better energy efficiency compared to processor based solutions can be achieved, for instance, when encryption is imposed by the application requirements

Towards the efficient use of LoRa for wireless sensor networks

Since their inception in 1998 with the Smart Dust Project from University of Berkeley, Wireless Sensor Networks (WSNs) had a tremendous impact on both science and society, influencing many (new) research fields, like Cyber-physical System (CPS), Machine to Machine (M2M), and Internet of Things (IoT). In over two decades, WSN researchers have delivered a wide-range of hardware, communication protocols, operating systems, and applications, to deal with the now classic problems of resourceconstrained devices, limited energy sources, and harsh communication environments. However, WSN research happened mostly on the same kind of hardware. With wireless communication and embedded hardware evolving, there are new opportunities to resolve the long standing issues of scaling, deploying, and maintaining a WSN. To this end, we explore in this work the most recent advances in low-power, longrange wireless communication, and the new challenges these new wireless communication techniques introduce. Specifically, we focus on the most promising such technology: LoRa. LoRa is a novel low-power, long-range communication technology, which promises a single-hop network with millions of sensor nodes. Using practical experiments, we evaluate the unique properties of LoRa, like orthogonal spreading factors, nondestructive concurrent transmissions, and carrier activity detection. Utilising these unique properties, we build a novel TDMA-style multi-hop Medium Access Control (MAC) protocol called LoRaBlink. Based on empirical results, we develop a communication model and simulator called LoRaSim to explore the scalability of a LoRa network. We conclude that, in its current deployment, LoRa cannot support the scale it is envisioned to operate at. One way to improve this scalability issue is Adaptive Data Rate (ADR). We develop two ADR protocols, Probing and Optimistic Probing, and compare them with the de facto standard ADR protocol used in the crowdsourced TTN LoRaWAN network. We demonstrate that our algorithms are much more responsive, energy efficient, and able to reach a more efficient configuration quicker, though reaching a suboptimal configuration for poor links, which is offset by the savings caused by the convergence speed. Overall, this work provides theoretical and empirical proofs that LoRa can tackle some of the long standing problems within WSN. We envision that future work, in particular on ADR and MAC protocols for LoRa and other low-power, long-range communication technologies, will help push these new communication technologies to main-stream status in WSNs