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

Internet of Things in agriculture, recent advances and future challenges

Soil water content (SWC) plays a key role in parƟ Ɵ oning water and energy fl uxes at the land surface and in controlling hydrologic fl uxes such as groundwater recharge. Despite the importance of SWC, it is not yet measured in an operaƟ onal way at larger scales. The aim of this study was to invesƟ gate the potenƟ al of wireless sensor network technology for the nearreal-Ɵ me monitoring of SWC at the fi eld and headwater catchment scales using the recently developed wireless sensor network SoilNet. The forest catchment Wustebach (?27 ha) was instrumented with 150 end devices and 600 EC-5 SWC sensors from the ECH 2 O series by Decagon Devices. In the period between August and November 2009, more than six million SWC measurements were obtained. The observed spaƟ al variability corresponded well with results from previous studies. The very low scaƩ ering in the plots of mean SWC against SWC variance indicates that the sensor network data provide a more accurate esƟ mate of SWC variance than disconƟ nuous data from measurement campaigns, due, e.g., to fi xed sampling locaƟ ons and permanently installed sensors. The spaƟ al variability in SWC at the 50-cm depth was signifi cantly lower than at 5 cm, indicaƟ ng that the longer travel Ɵ me to this depth reduced the spaƟ al variability of SWC. Topographic features showed the strongest correlaƟ on with SWC during dry periods, indicaƟ ng that the control of topography on the SWC paƩ ern depended on the soil water status. InterpolaƟ on results indicated that the high sampling density allowed capture of the key paƩ erns of SWC variaƟ on. AbbreviaƟ ons: AIC, Akaike informaƟ on criterion; SWC, soil water content; WI wetness index.

Potential of Wireless Sensor Networks for Measuring Soil Water Content Variability

Method and devices for use in a centralized wireless network are provided. The centralized wireless network employs a wireless communication protocol to communicate with various devices throughout the network. In addition to communication, the protocol may be used to control and monitor various aspects of the devices throughout the network.

Centralized wireless network for multi-room large properties

Nowadays, wireless sensor network (WSN) users are demanding more and more in terms of choice and diversity of applications. Hence, as the diversity of applications is increasing, it is worthwhile to propose a structure for the set of characterization parameters that allows sketching a taxonomy for WSN applications. This taxonomy is established via an application-oriented approach, identifying the specific services offered by each application. In this survey, we fill this gap in the WSN literature by describing the characterization parameters, organized into six different categories. Our taxonomy for application classification is centered on the different sets of parameters that have high impact on a given future WSN application. Typical attributes and values from related research works are considered as a reference, but in this survey, we propose inter- and intra-connections among the considered application groups. Based on these connections, new application groups have been proposed for applications that share common characterization parameters, along with a holistic overview of WSN application taxonomy and the discussion of the three generations of WSNs toward communication between things and the Internet of Things , as well as future trends for the development of WSN applications. Moreover, detailed parameters from different projects and authors in the field of WSNs are joined together for comparison purposes.

Survey on the Characterization and Classification of Wireless Sensor Network Applications

A wireless sensor network, a node device thereof and a method for arranging communications therein are presented. A first frequency is used in wireless communication of information between a headnode and subnodes of a first cluster (103) using a time slotted channel access scheme. A headnode of a second cluster (113) known the first frequency and selects a second, different frequency for use in wireless communication of information within said second cluster (113) using a time slotted channel access scheme. The headnode of the first cluster (103) is informed about the second frequency selected for the second cluster (113). Information from the headnode of said first cluster (103) to the headnode of said second cluster (113) is communicated on said second frequency, using the same time slotted channel access scheme as other nodes in said second cluster (113).

Energy efficient wireless sensor network, node devices for the same and a method for arranging communications in a wireless sensor network

This paper analyses the performance of IEEE 802.15.4 Low-Rate Wireless Personal Area Network (LR-WPAN) in a large-scale Wireless Sensor Network (WSN) application. To minimize the energy consumption of the entire network and to allow adequate network coverage, IEEE 802.15.4 peer-to-peer topology is selected, and configured to a beacon-enabled cluster-tree structure. The analysis consists of models for CSMA-CA mechanism and MAC operations specified by IEEE 802.15.4. Network layer operations in a cluster-tree network specified by ZigBee are included in the analysis. For realistic results, power consumption measurements on an IEEE 802.15.4 evaluation board are also included. The performances of a device and a coordinator are analyzed in terms of power consumption and goodput. The results are verified with simulations using WIreless SEnsor NEtwork Simulator (WISENES). The results depict that the minimum device power consumption is as low as 73 μW, when beacon interval is 3.93 s, and data are transmitted at 4 min intervals. Coordinator power consumption and goodput with 15.36 ms CAP duration and 3.93 s beacon interval are around 370 μW and 34 bits/s

Performance analysis of IEEE 802.15.4 and ZigBee for large-scale wireless sensor network applications

Finally a book on Wireless Sensor Networks that covers real world applications and contains practical advice! Kuorilehto et al. have written the first practical guide to wireless sensor networks. The authors draw on their experience in the development and field-testing of autonomous wireless sensor networks (WSNs) to offer a comprehensive reference on fundamentals, practical matters, limitations and solutions of this fast moving research area. Ultra Low Energy Wireless Sensor Networks in Practice: Explains the essential problems and issues in real wireless sensor networks, and analyzes the most promising solutions. Provides a comprehensive guide to applications, functionality, protocols, and algorithms for WSNs. Offers practical experiences from new applications and their field-testing, including several deployed networks. Includes simulations and physical measurements for energy consumption, bit rate, latency, memory, and lifetime. Covers embedded resource-limited operating systems, middleware and application software. Ultra Low Energy Wireless Sensor Networks in Practice will prove essential reading for Research Scientists, advanced students in Networking, Electrical Engineering and Computer Science as well as Product Managers and Design Engineers.

Ultra-Low Energy Wireless Sensor Networks in Practice: Theory, Realization and Deployment

Low energy consumption is a critical design requirement for most wireless sensor network (WSN) applications. Due to minimal transmission power levels, time-varying environmental factors and mobility of nodes, network neighborhood changes frequently. In these conditions, the most critical issue for energy is to minimize the transactions and time consumed for neighbor discovery operations. In this paper, we present an energy-efficient neighbor discovery protocol targeted at synchronized low duty-cycle medium access control (MAC) schemes such as IEEE 802.15.4 and S-MAC. The protocol effectively reduces the need for costly network scans by proactively distributing node schedule information in MAC protocol beacons and by using this information for establishing new communication links. Energy consumption is further reduced by optimizing the beacon transmission rate. The protocol is validated by performance analysis and experimental measurements with physical WSN prototypes. Experimental results show that the protocol can reduce node energy consumption up to 80% at 1-3m/s node mobility.

Mikko Kohvakka

Papers

Energy efficient wireless sensor network, node devices for the same and a method for arranging communications in a wireless sensor network

Performance analysis of IEEE 802.15.4 and ZigBee for large-scale wireless sensor network applications

Ultra-Low Energy Wireless Sensor Networks in Practice: Theory, Realization and Deployment

Energy-efficient neighbor discovery protocol for mobile wireless sensor networks

Ultra-Low Energy Wireless Sensor Networks in Practice