Data Mining - Concepts and Techniques.

The Internet of Things (IoT) provides a virtual view, via the Internet Protocol, to a huge variety of real life objects, ranging from a car, to a teacup, to a building, to trees in a forest. Its appeal is the ubiquitous generalized access to the status and location of any “thing” we may be interested in. Wireless sensor networks (WSN) are well suited for long-term environmental data acquisition for IoT representation. This paper presents the functional design and implementation of a complete WSN platform that can be used for a range of long-term environmental monitoring IoT applications. The application requirements for low cost, high number of sensors, fast deployment, long lifetime, low maintenance, and high quality of service are considered in the specification and design of the platform and of all its components. Low-effort platform reuse is also considered starting from the specifications and at all design levels for a wide array of related monitoring applications.

Design of a WSN Platform for Long-Term Environmental Monitoring for IoT Applications

https://digital.library.unt.edu/ark:/67531/metadc944353/m2/1/high_res_d/li_9144.pdf

Wireless Sensor Network System Design using Raspberry Pi and Arduino for Environmental Monitoring Applications

Due to recent advances in wireless communication technologies, there has been a rapid growth in wireless sensor networks research during the past few decades. Many novel architectures, protocols, algorithms, and applications have been proposed and implemented. The efficiency of these networks is highly dependent on routing protocols directly affecting the network life-time. Clustering is one of the most popular techniques preferred in routing operations. In this paper, a novel energy efficient clustering mechanism, based on artificial bee colony algorithm, is presented to prolong the network life-time. Artificial bee colony algorithm, simulating the intelligent foraging behavior of honey bee swarms, has been successfully used in clustering techniques. The performance of the proposed approach is compared with protocols based on LEACH and particle swarm optimization, which are studied in several routing applications. The results of the experiments show that the artificial bee colony algorithm based clustering can successfully be applied to WSN routing protocols.

Cluster based wireless sensor network routing using artificial bee colony algorithm

liams for their clarifi cation on state and national regulations aimed at reducing the risks of salmonellosis and their advice on conducting this survey. We also thank members and staff of the National Association of State Public Health Veterinarians and the National Resource Center for Health and Safety in Child Care and Early Education for their assistance. a population-based, case-control study.nas and Salmonella Marina infection in children: a refl ection of the increasing incidence of reptile-associated sal-monellosis in the United States. 6. Centers for Disease Control and Prevention. Multistate outbreak of human Salmonella Typhimurium infections associated with aquatic frogs—United States, Wild Boars as Hosts of Human-Pathogenic Anaplasma phagocytophilum Variants To the Editor: Michalik et al. (1) reported a 12% prevalence of Ana-plasma phagocytophilum, the caus-ative agent of human granulocytic anaplasmosis and tick-borne fever of ruminants, in wild boars in Poland. A. phagocytophilum has been reported with low prevalence among wild boar in the Czech Republic, Slovenia (2), and Japan (3). In Spain and Missis-sippi, United States, A. phagocyto-philum in wild boars or feral pigs, respectively , has not been reported (4,5). Furthermore, in Slovenia and Poland, the A. phagocytophilum gene sequences found in samples from wild boars were identical to those found in samples from humans and the tick vector Ixodes ricinus (1). These results suggested , as pointed out by Michalik et al. (1), that wild boar might play a role in the epizootiology of A. phagocyto-philum by serving as a natural reservoir host, at least in some regions. To test this hypothesis, we conducted transcriptomics studies to characterize host response to A. phagocy-tophilum infection in naturally and experimentally infected boars (6,7). The results suggested that boars are susceptible to A. phagocytophilum, but are able to control infection, mainly through activation of innate immune responses and cytoskeleton rearrangement to promote phagocy-tosis and autophagy. Control of A. phagocytophilum infection in boars might result in infection levels below PCR detection or infection clearance, contributing to the low percentage of infection prevalence detected for this species in most regions. The low detection levels suggest that boars have a low or no impact as a reservoir host for A. phagocytophilum. Even if boars remain persistently infected with A. phagocytophilum at low levels by downregulating some adap-tive immune genes and delaying the apoptotic death of neutrophils through activation of the Jak-STAT pathway, among other mechanisms (6), their role as a source of infection for …

In References to References

Wireless sensor networks (WSNs) have great potential to revolutionize many science and engineering domains. We present a novel environmental monitoring system with a focus on overall system architecture for seamless integration of wired and wireless sensors for long-term, remote, and near-real-time monitoring. We also present a unified framework for sensor data collection, management, visualization, dissemination, and exchange, conforming to the new Sensor Web Enablement standard. Some initial field testing results are also presented. The monitoring system is being integrated into the Texas Environmental Observatory infrastructure for long-term operation. As part of the integrated system, a new WSN-based soil moisture monitoring system is developed and deployed to support hydrologic monitoring and modeling research. This work represents a significant contribution to the empirical study of the emerging WSN technology. We address many practical issues in real-world application scenarios that are often neglected in the existing WSN research.

/pdf/integration-of-wireless-sensor-networks-in-environmental-1y7cdhdmjw.pdf

Integration of wireless sensor networks in environmental monitoring cyber infrastructure

We propose a spatial autocorrelation aware, energy efficient, and error bounded framework for interpolating maps from sensor fields. Specifically, we propose an iterative reporting framework that utilizes spatial interpolation models to reduce communication costs and enforce error control. The framework employs a simple and low overhead in-network coordination among sensors for selecting reporting sensors so that the coordination overhead does not eclipse the communication savings. Due to the probabilistic nature of the first round reporting, the framework is less sensitive to sensor failures and guarantees an error bound for all functional sensors for each epoch. We then propose a graceful integration of temporal data suppression models with our framework. This allows an adaptive utilization of spatial or temporal autocorrelation based on whichever is stronger in different regions of the sensor field. We conducted extensive experiments using data from a real-world sensor network deployment and a large Asian temperature dataset to show that the proposed framework significantly reduces messaging costs and is more resilient to sensor failures. We also implemented our proposed algorithms on a sensor network of MICAz motes. The results show that our algorithms save significant energy and the out of bound errors due to packet loss are below 5%.

/pdf/energy-efficient-map-interpolation-for-sensor-fields-using-2tkea8mnuk.pdf

Energy-Efficient Map Interpolation for Sensor Fields Using Kriging

Environmental monitoring represents a major application domain for wireless sensor networks. In this paper, we present the design and implementation of low-power wireless sensor networks for long-term, autonomous, and near-real-time environmental monitoring applications. We have developed a suite of networking protocols to provide reliable data collection with extremely low power consumption. A network of 35 sensor nodes has been deployed in a remote field station to monitor soil moisture along with other environmental parameters. The system has been integrated into the Texas Environmental Observatory infrastructure for long-term operation. Some field performance results are also presented to demonstrate the reliability and energy-efficiency of the network.

Design and implementation of low-power wireless sensor networks for environmental monitoring

Wireless sensor networks (WSN) technology has great potential to revolutionize many science and engineering domains. We present a novel environmental monitoring system with a focus on the overall system architecture for seamless integration of wired and wireless sensors for long-term, remote, and near-real-time monitoring. We also present a unified framework for sensor data collection, management, visualization, dissemination, and exchange, conforming to the new Sensor Web Enablement standard. Some initial field testing results are also presented.

An Environmental Monitoring System with Integrated Wired and Wireless Sensors

Environmental monitoring represents a major application domain for wireless sensor networks (WSN). However, despite significant advances in recent years, there are still many challenging issues to be addressed to exploit the full potential of the emerging WSN technology. In this dissertation, we introduce the design and implementation of low-power wireless sensor networks for long-term, autonomous, and near-real-time environmental monitoring applications. We have developed an out-of-box solution consisting of a suite of software, protocols and algorithms to provide reliable data collection with extremely low power consumption. Two wireless sensor networks based on the proposed solution have been deployed in remote field stations to monitor soil moisture along with other environmental parameters. As parts of the ever-growing environmental monitoring cyberinfrastructure, these networks have been integrated into the Texas Environmental Observatory system for long-term operation. Environmental measurement and network performance results are presented to demonstrate the capability, reliability and energy-efficiency of the network.

/pdf/design-and-implementation-of-large-scale-wireless-sensor-35xygpaiu8.pdf

Jue Yang

Papers

Integration of wireless sensor networks in environmental monitoring cyber infrastructure

Energy-Efficient Map Interpolation for Sensor Fields Using Kriging

Design and implementation of low-power wireless sensor networks for environmental monitoring

An Environmental Monitoring System with Integrated Wired and Wireless Sensors

Design and implementation of large-scale wireless sensor networks for environmental monitoring applications