Reino Virrankoski

Greenhouse Monitoring with Wireless Sensor Network

In modern greenhouses, several measurement points are required to trace down the local climate parameters in different parts of the big greenhouse to make the greenhouse automation system work properly. Cabling would make the measurement system expensive and vulnerable. Moreover, the cabled measurement points are difficult to relocate once they are installed. Thus, a wireless sensor network (WSN) consisting of small-size wireless sensor nodes equipped with radio and one or several sensors, is an attractive and cost-efficient option to build the required measurement system. In this work, we developed a wireless sensor node for greenhouse monitoring by integrating a sensor platform provided by sensinode Ltd. [1] with three commercial sensors capable to measure four climate variables. The feasibility of the developed node was tested by deploying a simple sensor network into Martens Greenhouse Research Foundations greenhouse in Narpio town in Western Finland. During a one day experiment, we collected data to evaluate the network reliability and its ability to detect the microclimate layers, which typically exist in the greenhouse between lower and upper flora. We were also able to show that the network can detect the local differences in the greenhouse climate caused by various disturbances, such as direct sunshine near the greenhouse walls. This article is our first step in the area of greenhouse monitoring and control, and it is all about the developed sensor network feasibility and reliability.

Distance Matrix Reconstruction from Incomplete Distance Information for Sensor Network Localization

This paper focuses on the principled study of distance reconstruction for distance-based node localization. We address an important issue in node localization by showing that a highly incomplete set of inter-node distance measurements obtained in ad-hoc node deployments carries sufficient information for the accurate reconstruction of the missing distances, even in the presence of noise and sensor node failures. We provide an efficient and provably accurate algorithm for this reconstruction, and we show that the resulting error is bounded, decreasing at a rate that is inversely proportional to radicn, the square root of the number of nodes in the region of deployment. Although this result is applicable to many localization schemes, in this paper we illustrate its use in conjunction with the popular multidimensional scaling algorithm. Our analysis reveals valuable insights and key factors to consider during the sensor network setup phase, to improve the quality of the position estimates

TASC: topology adaptive spatial clustering for sensor networks

The ability to extract topological regularity out of large randomly deployed sensor networks holds the promise to maximally leverage correlation for data aggregation and also to assist with sensor localization and hierarchy creation. This paper focuses on extracting such regular structures from physical topology through the development of a distributed clustering scheme. The topology adaptive spatial clustering (TASC) algorithm presented here is a distributed algorithm that partitions the network into a set of locally isotropic, non-overlapping clusters without prior knowledge of the number of clusters, cluster size and node coordinates. This is achieved by deriving a set of weights that encode distance measurements, connectivity and density information within the locality of each node. The derived weights form the terrain for holding a coordinated leader election in which each node selects the node closer to the center of mass of its neighborhood to become its leader. The clustering algorithm also employs a dynamic density reachability criterion that groups nodes according to their neighborhoods density properties. Our simulation results show that the proposed algorithm can trace locally isotropic structures in non-isotropic network and cluster the network with respect to local density attributes. We also found out that TASC exhibits consistent behavior in the presence of moderate measurement noise levels

Capacity for Spectrum Sharing Cognitive Radios with MRC Diversity at the Secondary Receiver under Asymmetric Fading

In this paper we study the capacity of spectrum sharing cognitive radios (CR) with Maximal Ratio Combining (MRC) diversity at the secondary receiver under asymmetric fading, where the channel from secondary transmitter to primary receiver suffer Nakagami-m fading while the one from secondary transmitter to its receiver follows Rayleigh Multipath fading. Our mathematical analysis and numerical results show that with MRC combining diversity at the secondary receiver, more capacity is achieved. In addition, when the SU

Localization Services for Online Common Operational Picture and Situation Awareness

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Capacity for Spectrum Sharing Cognitive Radios with MRC Diversity and Imperfect Channel Information from Primary User

-PU

IEC 61850 based smart grid security

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Stable transmission for a cognitive-shared channel with rechargeable transmitters

channel has less severe fading which strongly affects the capacity of CR channel, utilizing MRC combining technique for CR system could reduce the effects.

pRoot: An Adaptable Wireless Sensor-Actuator Hardware Platform

Many operations, be they military, police, rescue, or other field operations, require localization services and online situation awareness to make them effective. Questions such as how many people are inside a building and their locations are essential. In this paper, an online localization and situation awareness system is presented, called Mobile Urban Situation Awareness System (MUSAS), for gathering and maintaining localization information, to form a common operational picture. The MUSAS provides multiple localization services, as well as visualization of other sensor data, in a common frame of reference. The information and common operational picture of the system is conveyed to all parties involved in the operation, the field team, and people in the command post. In this paper, a general system architecture for enabling localization based situation awareness is designed and the MUSAS system solution is presented. The developed subsystem components and forming of the common operational picture are summarized, and the future potential of the system for various scenarios is discussed. In the demonstration, the MUSAS is deployed to an unknown building, in an ad hoc fashion, to provide situation awareness in an urban indoor military operation.

Recursive clock skew estimation for wireless sensor networks using reference broadcasts

In this paper we study the capacity of spectrum sharing cognitive radios (CR) with Maximal Ratio Combining (MRC) diversity at the secondary receiver under Rayleigh fading. The secondary user does not have perfect channel information of SU