Gabriel Mujica

Wireless Sensor Network for Environmental Monitoring: Application in a Coffee Factory

Wireless sensor networks have been a big promise during the last few years, but a lack of real applications makes difficult the establishment of this technology. In this paper a real monitoring application in an instant coffee factory is presented. This application belongs to the group of environmental solutions based on wireless sensor networks, and it is focused on the impact of the instant coffee production processes in one of the largest instant coffee factories in Europe. The paper includes the entire application scenario, from the hardware of the WSN nodes to the software that will evaluate the impact and will close the loop.

Modelling and planning reliable wireless sensor networks based on multi-objective optimization genetic algorithm with changeable length

Wireless sensor networks (WSN) have shown their potentials in various applications, which bring a lot of benefits to users from different working areas. However, due to the diversity of the deployed environments and resource constraints, it is difficult to predict the performance of a topology. Besides the connectivity, coverage, cost, network longevity and service quality should all be considered during the planning procedure. Therefore, efficiently planning a reliable WSN is a challenging task, which requires designers coping with comprehensive and interdisciplinary knowledge. A WSN planning method is proposed in this work to tackle the above mentioned challenges and efficiently deploying reliable WSNs. First of all, the above mentioned metrics are modeled more comprehensively and practically compared with other works. Especially 3D ray tracing method is used to model the radio link and sensing signal, which are sensitive to the obstruction of obstacles; network routing is constructed by using AODV protocol; the network longevity, packet delay and packet drop rate are obtained via simulating practical events in WSNet simulator, which to the best of our knowledge, is the first time that network simulator is involved in a planning algorithm. Moreover, a multi-objective optimization algorithm is developed to cater for the characteristics of WSNs. Network size is changeable during evolution, meanwhile the crossovers and mutations are limited by certain constraints to eliminate invalid modifications and improve the computation efficiency. The capability of providing multiple optimized solutions simultaneously allows users making their own decisions, and the results are more comprehensive optimized compared with other state-of-the-art algorithms. Practical WSN deployments are also realized for both indoor and outdoor environments and the measurements coincident well with the generated optimized topologies, which prove the efficiency and reliability of the proposed algorithm.

Hardware-software integration platform for a WSN testbed based on cookies nodes

In this work a complete hardware-software support platform for a WSN testbed focused on developing wireless sensor applications in a simple and intuitive way is presented, as an alternative of commercial-motes-based testbeds that can be found in the state of the art. The main target of this hardware-software platform is to provide the highest abstraction level on the management of WSNs but in the simplest way in order to achieve a fast profiling mechanism for reliable prototyping based on the Cookies platform as well as helping users to develop, test and validate Cookie-Based WSN applications.

Simulation tool and case study for planning wireless sensor network

In this paper, a simulation tool for assisting the deployment of wireless sensor network is introduced and simulation results are verified under a specific indoor environment. The simulation tool supports two modes: deterministic mode and stochastic mode. The deterministic mode is environment dependent in which the information of environment should be provided beforehand. Ray tracing method and deterministic propagation model are employed in order to increase the accuracy of the estimated coverage, connectivity and routing; the stochastic mode is useful for large scale random deployment without previous knowledge on geographic information. Dynamic Source Routing protocol (DSR) and Ad hoc On-Demand Distance Vector Routing protocol (AODV) are implemented in order to calculate the topology of WSN. Hence this tool gives direct view on the performance of WSN and assists users in finding the potential problems of wireless sensor network before real deployment. At the end, a case study is realized in Centro de Electronica Industrial (CEI), the simulation results on coverage, connectivity and routing are verified by the measurement.

Integrated Toolset for WSN Application Planning, Development, Commissioning and Maintenance: The WSN-DPCM ARTEMIS-JU Project

In this article we present the main results obtained in the ARTEMIS-JU WSN-DPCM project between October 2011 and September 2015. The first objective of the project was the development of an integrated toolset for Wireless sensor networks (WSN) application planning, development, commissioning and maintenance, which aims to support application domain experts, with limited WSN expertise, to efficiently develop WSN applications from planning to lifetime maintenance. The toolset is made of three main tools: one for planning, one for application development and simulation (which can include hardware nodes), and one for network commissioning and lifetime maintenance. The tools are integrated in a single platform which promotes software reuse by automatically selecting suitable library components for application synthesis and the abstraction of the underlying architecture through the use of a middleware layer. The second objective of the project was to test the effectiveness of the toolset for the development of two case studies in different domains, one for detecting the occupancy state of parking lots and one for monitoring air concentration of harmful gasses near an industrial site.

Performance evaluation of an AODV-based routing protocol implementation by using a novel in-field WSN diagnosis tool

The Wireless Sensor Network research field has been growing and becoming more mature during the last decade since novel technologies and research lines have emerged targeting its usability in the real world under different application scenarios. One of the key topics to assure the efficiency and effectiveness of these technologies in final applications is the communication and routing strategies within the WSN. In this context, it is essential to evaluate and validate the implementation of routing algorithms and network connectivity in real deployments, as a support of theoretical simulation models that cannot predict certain constraints and limitations in the behavior of the system. In this way, a real implementation of a flexible AODV-based routing protocol using a modular HW-SW node platform is proposed in this work, in addition to its practical assessment under real conditions by using a novel in-situ WSN evaluation tool. This tool has been created to support users during the deployment analysis and diagnosis in real environments, beyond the typical study of routing performance through WSN simulators.

On-the-fly dynamic reprogramming mechanism for increasing the energy efficiency and supporting multi-experimental capabilities in WSNs

Remote reprogramming capabilities are one of the major concerns in WSN platforms due to the limitations and constraints that low power wireless nodes poses, especially when energy efficiency during the reprogramming process is a critical factor for extending the battery life of the devices. Moreover, WSNs are based on low-rate protocols in which as greater the amount of data is sent, the more the possibility to lose packets during the transmitting process is. In order to overcome these limitations, in this work a novel on-the-fly reprogramming technique for modifying and updating the application running on the wireless sensor nodes is designed and implemented, based on a partial reprogramming mechanism that significantly reduces the size of the files to be downloaded to the nodes, therefore diminishing their power/time consumption. This powerful mechanism also addresses multi-experimental capabilities because it provides the possibility to download, manage, test and debug multiple applications into the wireless nodes, based on a memory map segmentation of the core. Being an on-the-fly reprogramming process, no additional resources to store and download the configuration file are needed.

Deployment Strategies of Wireless Sensor Networks for IoT: Challenges, Trends, and Solutions Based on Novel Tools and HW/SW Platforms

The research field of wireless sensor networks has experimented an incredible growth during the last 10 years along with the progressive inclusion of the Internet of Things (IoT) as the main foundations for the future of the smart and sustainable cities. The essence of a WSN as a self-organized distributed system based on low-power autonomous sensor nodes has envisioned the creation of novel solutions that cover multi-domain areas related to embedded computing architectures, telecommunications, microelectronics, and industrial technologies. However, this innovation process also implies new challenges and more complexity when designing and implementing smart applications based on this technology, from the requirement stage up until the final operational release of the system. This is particularly important during the deployment, commissioning, and in-field validation phases as a fundamental part to analyze and optimize the real behavior of the network with respect to what is expected from the theoretical simulation/planning models. In this chapter, a new perspective of WSN deployment strategies for IoT application scenarios is presented, trying to cope with today’s lack of well-defined frameworks and methodologies to efficiently carry out the commissioning, configuration, and on-site performance assessment tasks. New trends and solutions based on hardware–software support tools are discussed so as to provide an overall approach for accomplishing effective wireless distributed sensor deployments.

A novel on-site deployment, commissioning and debugging technique to assess and validate WSN based smart systems

In this work a novel on-site toolset-based architecture for tackling the main challenges of deploying and commissioning large scale WSN-based systems is proposed. This is one of the first implementations that addresses a complete set of runtime algorithms to efficiently deploy sensor platforms in the target scenarios based on the inclusion of the real behavior of the nodes within the in-situ simulation chain, combined with the integration of runtime diagnosis and reprogramming strategies to analyze the performance of the deployment in-field.

Radio propagation modeling and real test of ZigBee based indoor wireless sensor networks

Abstract The deployment of nodes in Wireless Sensor Networks (WSNs) arises as one of the biggest challenges of this field, which involves in distributing a large number of embedded systems to fulfill a specific application. The connectivity of WSNs is one of the main issues to assure the efficiency of the system implementation and the quality of the service of the deployment, which is difficult to estimate due to the diversity and irregularity of the applied environment and it affects the WSN designers’ decision on deploying sensor nodes. Therefore, in this paper, a new method is proposed to enhance the efficiency and accuracy on ZigBee propagation modeling and simulation in indoor environments. The method consists of two steps: automatic 3D indoor reconstruction and 3D ray-tracing based radio simulation. The automatic 3D indoor reconstruction employs unattended image classification algorithm and image vectorization algorithm to accurately build the environment database, which also significantly reduces time and efforts spent on non-radio propagation issues. The 3D ray tracing is developed by using a kd-tree space division algorithm and a modified polar sweep algorithm, which accelerates the searching of rays over the entire space. A ZigBee signal propagation model is proposed for the ray-tracing engine by considering both the materials of obstacles and the impact of positions along the ray path of the radio. Three different WSN deployments are realized in the indoor environment of an office and the simulation results are verified to be accurate. Experimental results also indicate that the proposed method is efficient in the pre-simulation strategy and the 3D ray searching scheme, and it is robust for different indoor environments.