Wireless sensor networks (WSNs) consist of a large number of small devices or nodes, called micro controller units (MCUs) and located in homes and/or offices, to be operated through the internet from anywhere, making these devices smarter and more efficient. Quality of service routing is one of the critical challenges in WSNs, especially in surveillance systems. To improve the efficiency of the network, in this article we proposes a distributed learning fractal algorithm (DFLA) to design the control topology of a wireless sensor network (WSN), whose nodes are the MCUs distributed in a physical space and which are connected to share parameters of the sensors such as concentrations of C O 2 , humidity, temperature within the space or adjustment of the intensity of light inside and outside the home or office. For this, we start defining the production rules of the L-systems to generate the Hilbert fractal, since these rules facilitate the generation of this fractal, which is a fill-space curve. Then, we model the optimization of a centralized control topology of WSNs and proposed a DFLA to find the best two nodes where a device can find the highly reliable link between these nodes. Thus, we propose a software defined network (SDN) with strong mobility since it can be reconfigured depending on the amount of nodes, also we employ a target coverage because distributed learning fractal algorithm (DLFA) only consider reliable links among devices. Finally, through laboratory tests and computer simulations, we demonstrate the effectiveness of our approach by means of a fractal routing in WSNs, by using a large amount of WSNs devices (from 16 to 64 sensors) for real time monitoring of different parameters, in order to make efficient WSNs and its application in a forthcoming Smart City.

No abstract

No abstract

Systems science. A scientific field to research taxonomies, concepts, theories, and methodologies. According to [6] the field of scientific inquiry whose objects of study are systems. Variety. Number of possible states that a system is capable of exhibiting [7]. Viability. The ability of a system to maintain a separate existence [7]. Viable system model (VSM). According to [2], is a system able to maintain a separate existence, capable of maintaining its identity and transcend independently. Systems science uses the construction of models to represent real systems; for example, the viable system model (VSM) was elaborated by Beer [7] to represent human activity systems like as SCM.

In the present document we present an Interface called BrainMouse where its main task is to help people with motor disabilities specially tetraplegic or quadriplegic people that they can move the mouse of the computer by means of blinking or any neural response. The Interface uses the data obtained from a neuronal system which is responsible for taking reliable readings of the electrical signals generated in the human brain, through non-intrusive neuronal interfaces. The recorded data is used by the BrainMouse Interface so that the mouse can perform functions such as an up, down, left lateral, right lateral, left click, right click and double click. Thus, this interface has all the options that a conventional mouse would have.