Additionally, a multiple reception scheme based on C2DMA system was presented in Reception of Multiple Users in Reconfigurable Networks  and published in Ad-Hoc and Sensors WirelessNetworks magazine, it compares the traditional DS-CDMA, using different families of codes, and C2DMA models in multi-user scenarios where hidden and exposed ter- minal interference are presented. The results showed that the traditional DS-CDMA model is vulnerable to hidden terminal interference and robustness to exposed terminal interference. In this model, the spreading codes cannot help to mitigate hidden terminal interference because it is a vulnerability model. On the other hand, C2DMA model showed robustness to hidden and exposed terminal interference, hence the properties of spreading codes play a crucial role. This feature permits the multiple reception of signal simultaneously what is attractive to RWN. Finally, an exhaustive search of codes is presented from sequence with length N = 8. It considers useful properties of sequences for both systems, traditional DS-CDMA and C2DMA, such as No negative, balance, correlation, and shifting and some highlights from sequences with length N = 16. This way, new code sets are provided for both CDMA models in order to incorporate them to future applications.
LoRa : LoRa as a wireless technology, based on the Sub-GHz band to make it easier to communicate with the lower power consumption, can be used by battery- powered or other energy collection way of power supply. Lower data rates also extend battery life and increase network capacity. LoRa signal on the building penetration is also very strong. LoRa have technical features more suitable for low- cost large-scale Internet of things deployment. 
Xbee motes could be a good solution for wireless monitoring in refrigerated industrial environments, because the rate of lost packets inside the cargo (0.26%) is always lower than that of Xbow (4.74%). For the latter, a large quantity of lost packets is found at singular moments, which never occur for Xbee motes. The better reliability of the Xbee motes corresponds with their higher RF power. However, a potential concern in the Xbee based prototype is the large battery size, which makes the system much bigger than the Xbow motes.
The design of a wireless ad hoc network has to take into account several in- teresting and difficult problems. Traditional wireless communication problems related to the physical medium, such as low transmission rate, high bit error rates, noise, limited range, and significant variation in physical medium condi- tions, must be overcomed. In the MAC sublayer, the difficulty of collision detec- tion and the hidden and the exposed terminal problems demand new medium access algorithms. Moreover, as wireless ad hoc nodes may move arbitrarily and the status of the communication links between the nodes may vary, routing protocols proposed for wired networks are not suited for operation in wireless ad hoc networks. Several routing protocols have been proposed to cope with the various challenges of ad hoc networks. At the transport layer, TCP-like trans- port protocols also present several problems when used on wirelessnetworks. High bit-error rates and frequent route failures reduce TCP performance, de- manding modifications to TCP or the design of new transport protocols.
The wireless sensor network is quite different from the traditional wirelessnetworks . It has a large number of sensor nodes and they are densely de- ployed. The distance between neighbor nodes is shorter compared to other wire- less networks. The data rate and mobility in the wireless sensor network are low. Because of the remote nature and the size of the individual nodes, they rely on limited battery energy that cannot be replenished for most wireless sen- sor networks. In many cases, sensor nodes are placed in the field for years at a time without maintenance or human intervention of any kind. Thus, low power consumption technology is a major issue in wireless sensor networks in order to prolong system lifetime.
devices also create noise that impacts in the communication of a sensor network. Moreover, because of the limitations of sensor nodes, their radios are more susceptible to noise and interference than those of other wireless technologies. Consequently, the effects of these factors on the quality and stability of the sensor networks are even more severe. The wireless communication standards usually consist of a set of discrete channels, allowing multiple wirelessnetworks operating on the same frequency band, where each utilizes a single channel or a subset of them. However, current sensor networks do not have the ability to determine which channels are not in use, as well as they cannot detect the current conditions at the deployment environment, i.e., WSN cannot evaluate the quality of the different channels. This means that they do not have the mechanisms to deal with noisy environments and interferences. This section presents our studies and proposals for this problem. In particular, the next sub-section summarizes our empirical studies on the quality of different channels of IEEE802.15.4 compliant sensor networks in different environments.
We have propose an event-driven field estimation scheme for wireless sensor networks . Differing from the above discussed approaches, our scheme re- duces the amount of transmitted data by sending only part of the samples. The assumption behind our scheme is that although we have to sample the process with its required temporal frequency to avoid losing important data, not all the samples will bring interesting information. Hence, the proposed scheme exploits specific features of the monitored processes in order to reduce the amount of data transmitted to the sink. Each sensor node collects the samples and decides to only send to the ones considered an event of interest to itself. This mimics an event-driven system over a continuous-data transmission application.
The spectrum sensing functionality in CWSNs is implemented using the information that the wireless interfaces offer to us. For example, if a cognitive device has only one WiFi interface we can extract from it information such the Received Signal Strength Indication (RSSI) or the link quality. These interfaces work in the ISM bands (2.4 GHz, 868 MHz and 434 MHz). The algorithm can change when the scanning task is executed, but the interface limitations should be taken into account. Another key aspect of CWSNs is the mobility of the nodes. In contrast to original cognitive scenarios, the nodes of these networks can be mobile. Despite this is not a widespread situation in WSN applications, the possibility of movement exists. For example, in robotic applications, where each node is installed in a mobile robot. Another example is the assembly line monitoring, where a sensing device follows the building process of a product in a linear movement.
has proposed a smart city model including six key sectors: smart economy, smart mobil- ity, smart environment, smart people, smart living and smart governance. From this list, European cities are mainly implementing smart environment and smart mobility . From a technological point of view, information systems are being deployed to transform infrastructure management towards a data-driven approach following four basic building blocks: data, analysis, feedback and adaptability . In order to feed the information systems, smart cities use elements of the Internet of things (IoT) as the main data source, such as mobile phones, radio-frequency identification (RFID) cards and wireless sensor networks (WSNs). The data collected by the latter are used in a plethora of applications. For example, traffic monitoring sensors are used to control traffic lights  and wireless meters are installed in pipes to monitor leaks and ruptures . Moreover, these data give city managers and other stakeholders the opportunity to plan future facilities based on a better picture of citizens’ behavior and the real use of the current infrastructures. The clear benefits provided by smart city technology have prompted many cities to devote a considerable part of their innovation efforts to developing their concept of smart city. This has caused a significant and rapid increase in the number of WSN deployments on the streets, which has resulted in the emergence of new applications with many different technologies, solutions, requirements, etc.
Abstract. This work has considered the development, testing, configuration and implementation of a wireless sensor network infrastructure. This infrastructure on a testbed scale has been used primarily for research, oriented to an interdisciplinary approach that encompasses the hardware, software, algorithms and data. It sought to demonstrate that the heterogeneity of devices and small existing structures may coalesce into well-organized, large-scale, different existing grids that will enable a quantitative and qualitative research to a much larger scale by addressing the dynamic changes of venues, infrastructure and composition of nodes. Considering that a real implementation is usually a complicated task, we have performed a network simulation and a real testbed. Also a contribution to the establishment of a global network of wireless sensors has been highlighted, distinguishing three sub domains in the global network considered: the existing top network, the sensing devices and the servers.
An Intelligent Car Park Management System based on Wireless Sensor Networks: En este proyecto se utiliza una plataforma hardware de la compañía Crossbow, los cuales se los ubica en cada espacio de estacionamiento como motas estas funcionan en el estándar IEEE 802.15.4, se organizan en una red mesh con el uso de gateways de borde, los mismos que hacen la conexión con un servidor y base de datos que hará la interacción con el cliente, además poseen una pantalla de visualización y control la cual muestra el estado del sistema en tiempo real ( ❄ ). Design and Implementation of a prototype Smart Parking (SPARK) System using Wireless Sensor Networks: El sistema SPARK consta de 6 subsistemas que son: Subsistema RSI, Recolección de datos, Administración de estacionamiento, Sub- sistema de guía, Visualización en la entrada y subsistema del cliente, los cuales en integración se encargan de trasmitir la información de los espacios de estacio- namiento para luego reunirlos en una base de datos, administrarlos y hacer aplica- ciones para el usuario como: Displays de visualización, LEDs indicadores, SMS y un servidor de administración. Utilizan hardware de Crossbow y en los estándares Wi-Fi y ethernet ( ❄ ).
The traditional network layer methods based on the end- to-end path discovery, resources reservation along the discovered path, and path recovery in case of topological changes are not suitable for WSN with similar characteristics to ours for several reasons. To begin with, the time wasted in the path discovery is not acceptable for urgent non-periodic (event-driven) packets. In addition, it is not convenient to reserve resources for the unpredictable non-periodic packets. Even for periodic continuous flows, these methods are not practical in dynamic WSN since service disruption during the path recovery increases the data delivery delay which is not acceptable in our mission critical application. Finally, the end-to-end path based approaches are not scalable due to huge overhead of path discovery and recovery in large scale sensor networks. As an alternative to the inefficient reservation-based approaches, the network layer will include an end-to-end QoS provisioning method based on local decisions at each intermediate node without path discovery and maintenance.
Wireless visual sensor network is a particular type of wireless sensor networks which includes some nodes that are equipped with visual sensors. These visual sensors nodes are responsible for capturing images of targets. They have a unique feature that the targets covered by the camera can be as far away from nodes as they can capture images of targets that are not necessarily in the camera’s vicinity. Thus, wireless visual sensor networks are widely used for popular consumer application such as public security, facilities surveillance and monitoring. Most applications of surveillance networks, including event detecting and reporting, rely on the knowledge of target position . Localization is an important part in visual sensor networks, since it provides with coordinates for both sensors and the targets in sensor networks . In this paper, we focus on the problem which the sensor locations are already known. Approaches for sensor node localization, such as received-signal-strength (RSS) , can not solve the problem of target localization, because targets are usually passive and un-cooperative in localization. Our objective is to localize a target in the sensing field. Target localization is a technique that is used to estimate a target’s position and merge the information regarding location and orientation of other cameras for effective handoff . Generally, researches  on target localization in camera sensor networks are based on accurate image processing, and the position of the target can be extracted perfectly. However, vision-based target localization in camera sensor networks will face a great challenge. First of all, in wireless visual sensor networks, visual sensor node is usually equipped with a low-resolution camera due to the cost limitation . Secondly, the image processing on the sensor node is a work of great challenge. Camera sensors generate a huge amount of data compared to scalar sensors. Such data processing is in general computationally expensive, requires floating point arithmetic, and is costly to implement locally . Thirdly, although the central nodes or the base stations in the visual sensor network have more powerful compute capabilities, transmitting the
We have mentioned that SCADAs used to be really complex and expensive programs with proprietary hardware, software and communication protocols. Currently, new open alterna- tives that make use of the common Internet protocols (TCP/IP), have proven to be a feasible solution. They offer flexibility and can work over previously existing networks and there- fore can be accessed from any place where there is an Internet connection without the need to install and configure complex programs. In general terms, the architecture proposed in this section makes use of an open-source web-based SCADA, called Mango, which proves that the use of this kind of system in the CIP context is feasible, cost-efficient, easily accessi- ble and simple to use. Regarding the SCADA-WSAN connection, the WSAN and SCADA communication has been decoupled by means of a gateway. The gateway is in charge of gathering the information from the WSAN and retransmitting it to the SCADA. Conversely, the gateway receives requests from the SCADA and processes them, disseminating the cor- responding information into the WSAN. Figure 7.2 shows the general architecture of the system. The operator accesses the web-based SCADA through a conventional browser. The SCADA receives all the information from the gateway and stores it in a database. In a similar way the gateway collects all the information from the WSAN before sending it to the SCADA. The system supports the use of multiple gateways and, therefore, can receive information from a large number of disjoint WSANs.
New standards may introduce changes in the behavior of the devices that are part of the system (e.g. mobile phones and their internal components) mainly due to the modulation schemes they use, generating nonlinearities in the be- havior and memory effects (when an output signal depends on past values of an input signal). Memory effects in the time-domain cause the output of an elec- tronic device to deviate from a linear output when the signal changes, resulting in the deterioration of the whole system performance since the device begins behaving nonlinearly. In this work we are interested in modeling the nonlinear behavior that an amplifier can have inside a wireless transmission.
Some telemedicine services require real-‐time communications capabilities to support high-‐resolution applications, needed for streaming medical video and audio (Vergados, 2007), therefore, the use of broadband wireless alternatives have been proposed to the deployment of RTWN. The proposals comprise long-‐range technologies, such as the IEEE 802.16 for Metropolitan Area Networks (Mandioma et al., 2007; Ying Su & Caballero, 2010), cellular communication systems for Wide Area Networks (Meethal & J., 2011; Mulvaney et al., 2010; Zhu & Dong, 2011) and the VSAT networks for Broadband Satellite Communications (Chorbev et al., 2008; Ibikunle, 2009; Su & Soar, 2010). The WAN alternatives tend to be used as standalone last-‐mile solutions, since its coverage ratio directly depends on previously deployed network infrastructure. Differently, the BSC alternative provides an unlimited coverage ratio to the deployment of network communications that are typically implemented in high budget telemedicine projects. According to the World Health Organization, the financial costs on deployment of RTWN represents an important barrier to enable telemedicine service delivery, since most of the project initiatives on rural telemedicine are limited in funding (World Health Organization, 2010b). Hence, the high-‐costs involved in the deployment and operation of wireless communications for rural areas, such as BSC solutions, may become a critical barrier for its broad implementation (Moffatt & Eley, 2011; Shakeel et al., 2001). This is particularly true for long-‐term telemedicine initiatives where funding is limited. Despite previously mentioned proposals that have been successfully deployed as RTWN, they may also be limited by the available rural infrastructure. This implies that such network architecture may not consider particularities of rural scenarios (e.g. distance between rural clinic and urban hospitals, or telemedicine traffic profiles based on rural characteristics, among others), nor a network protocol framework designed to enable telemedicine service delivery with quality of service provisioning in rural regions.