WINSOC is a Specific Targeted Research Project co-funded by the INFSO DG of the European Commission within the RTD activities of the Thematic Priority Information Society Technologies. WINSOC explores the possibility to develop a novel technology for Wireless Sensor Networks, that has significant potentials for overcoming conventional technologies in terms of cost, size and power consumption.WINSOC is a Specific Targeted Research Project co-funded by the INFSO DG of the European Commission within the RTD activities of the Thematic Priority Information Society Technologies.
WINSOC explores the possibility to develop a novel technology for Wireless Sensor Networks, that has significant potentials for overcoming conventional technologies in terms of cost, size and power consumption. The key idea of WINSOC is the development of a totally innovative design methodology, mimicking biologically systems, where the high accuracy and reliability of the whole sensor network is achieved through a proper interaction among nearby, low cost, sensors. This local interaction gives rise to distributed detection or estimation schemes, more accurate than that of each single sensor and capable to achieve globally optimal decisions, without the need to send all the collected data to a fusion center. The whole network is hierarchical and composed of two layers: a lower level, composed of the low cost sensors, responsible for gathering information from the environment and producing locally reliable decisions, and an upper level, composed of more sophisticated nodes, whose goal is to convey the information to the control centers.
The key point is the interaction among the low cost sensors that increases the overall network reliability, it decreases the probability of congestion around the sink nodes, it provides scalability and tolerance against breakdown or stand-by of some sensors, necessary for battery recharge.
Wireless sensor networks are currently receiving huge attention as a basic tool to detect emergency events or monitor physical parameters of interest, such as radiation, pollution, temperatures, pressures, and so on.
The key idea of WINSOC is the development of a totally innovative design methodology, mimicking biological systems, where the high accuracy and reliability of the whole sensor network is achieved through a proper interaction among nearby, low cost, sensors. This local interaction gives rise to distributed detection or estimation schemes, more accurate than that of each single sensor and capable of achieving globally optimal decisions, without the need to send all the collected data to a fusion center. The whole network is hierarchical and composed of two layers: a lower level, composed of the low cost sensors, responsible for gathering information from the environment and producing locally reliable decisions, and an upper level, composed of more sophisticated nodes, whose goal is to convey the information to the control centers.
The key issue is the interaction among nearby, low cost, sensors in a way that increases the overall network reliability, decreases the probability of congestion around the sink nodes, provides scalability and tolerance against breakdown or stand-by of some sensors, and eliminate the necessity for battery recharge. Building on this idea, the consortium has put together expertise from large companies, academies, research centres, end-users and SME’s, to create a strong synergism between the academic world, industries and end-users. The goal is, on one side, to develop a general purpose innovative wireless sensor network having distributed processing capabilities and, on the other side, to test applications on environmental risk management where heterogeneous networks, composed of nodes having various degree of complexity and capabilities, are made to work under realistic scenarios. More specifically, the project will address applications to small landslide detection, gas leakage detection and large scale temperature field monitoring.
Scrutinizing the state of the art of the paradigms typically employed in sensor networks, it is possible to recognise a common critical factor: the current paradigms greatly reflect (although scaled and adapted) a well known and consolidated methodological approach borrowed from TLC networks, which however has been developed to cope with totally different requirements and constraints, with respect to a sensor network. The most typical solutions try to adapt classical telecommunication protocols, except for a much greater emphasis on energy-efficient design (see, e.g., ZigBee). However, they still require rather sophisticated network protocols and management overheads in applications where the bit rate required by the sensor network is relatively small and what is really necessary is only to bring the event of interest from the source to the right control node. Typically, the congestion around the sink nodes is only alleviated, but not avoided and the network is not scalable.
In WINSOC, we envisage the development of a very innovative concept of sensor network that represents a significant departure from current proposals. The network is organized in two hierarchical levels. At the low level, there are very simple nodes that gather relevant information and interact with each other to achieve a consensus about the locally observed phenomenon. The interaction occurs through a very simple mechanism that does not require complicated modulation, MAC, or routing strategies. This interaction among the sensors is the key feature, as it improves the reliability of the local decisions and, at the same time, it yields fault tolerance and scalability. The decisions taken locally are then communicated to the upper level nodes that take care of forwarding them to the appropriate control centers.
Building on this fundamental structure, WINSOC has the following primary objectives:
AMRITA University’s landmark wireless sensor network system for landslide detection deployed at anthoniar colony, munnar, warns of a possible landslide considering the torrential rains that have been falling through this region and the state of Kerala. This wireless sensor system, which is the first in India, has detected certain signals that indicate vulnerability of this region to possible landslides and the signals have been made available online at the website, and thereby researchers across the world can study the signal variations and patterns on a real-time basis.
On July 21, the data analysis shows increase in pore pressure and also noticeable soil movements. The authorities and the district collector have been notified accordingly and AMRITA has requested the government authorities to issue an advisory to the people of this region to relocate to another area till the region comes back to normalcy in terms of pore pressure and underneath soil movements. A team of researchers from AMRITA are currently working on exact measurement details on site as well as closely monitoring at the data centre in Amritapuri (Kollam) campus of AMRITA University. Any updates would be informed to the concerned authorities from the state of the art Wireless Sensor Network laboratory at Amritapuri.
AMRITA’s system which is deployed at anthoniar colony, munnar, Idukki district of Kerala, consists of 50 geological sensors and 10 Wireless sensor nodes. The system is functional from june 2009 in an area which is very prone to rainfall-induced landslides. In the past, landslides at munnar have caused considerable losses to human life. The deployment of this system has come as a lifeline for this region. This technological breakthrough system was developed as part of the research project “WINSOC” (wireless sensor network with self organization capabilities for critical and emergency applications), which is co-funded by INFSO DG of European commission. The project consist of a consortium of 11 partners from 8 different countries. AMRITA University and ANTRIX (the commercial arm of indian space research organization) are the only partners participating from india, and all other partners are from Europe.
This system can also be suitably modified for applications to gas leakage detection, avalanche and large scale temperature field monitoring (forest fire detection). Within the next 3 months , AMRITA has plans to extend this network to 150 geological sensors and 25 wireless sensor nodes as part of the research funding provided by Department of Information Technology of the Government of India. These sensors will also be deployed at various sensitive locations in other parts of the country. Dr. Maneesha V Ramesh, head of the centre at amritapuri campus and the principal investigator of this project, is currently in Canada touring universities, and in fact was able to analyze all of the signals live on the internet to arrive at landslide possibility
In the WINSOC approach, sensor nodes communicate with their neighbors to arrive at a consensus on what has been sensed, developed by INFO. The network then finds the best path through the available nodes to relay this information to the control centre.
This biological principle is being tested in the landslide detection system developed by AMRITA. A prototype network of geological sensors has been installed in the Idduki rainforest of Kerala, India, a region vulnerable to landslides in the monsoon season.
A prototype wireless sensor node has been developed as part of WINSOC project. SELEX has already sent approximately 15 nodes to AMRITA and CCSS. These nodes will be integrated, deployed, tested and verified in both landslide detection scenario and forest fire scenario.
The Wireless Node is composed of three principal entities:
The node satisfies different environmental requirements (temperature, humidity, salty fog, rain, sand and dust; shock, fall and vibrations; electro-magnetic emissions) as the ones specified in many standards defined by ETSI, IEC and others. The node interacts with sensors by means of an external board (called Expansion Board) whose task is to adapt different sensors’ outputs to the RS485 serial bus of the Winsoc Node.
A subset of nodes have been developed with miniaturized antennas instead of dipole ones. Selex Communications has been responsible for the development of nodes, both from HW and SW point of view.
CCSS has developed the expansions boards and the communication protocol between node and the board. Cea-Leti has developed the miniaturized antennas.
India’s First Ever Wireless Sensor Network for Landslide Detection
The devastation and loss of life caused by landslides affects hundreds of people every year around the world. AMRITA University of India has deployed India’s first landslide detection system using wireless sensor network at Munnar, Idukki, Kerala, India.
Amrita University’s rainfall induced landslide detection system uses heterogeneous network that includes wireless sensor networks in combination with Wi-Fi and satellite technology. The test bed deployment site chosen for this study is highly prone to landslides due to systemic monsoon induced rainfalls in the region.
The actual deployment site is in the Idukki district of the southern state of Kerala, India. The existing infrastructure at Munnar provides the infrastructure needed for retrieving geological and hydrological data from the field and the data is transmitted long distant for further analysis. The data received from the geophysical sensors are transmitted through the wireless sensor network which uses a two layer hierarchical topology.
Multiple sets of geophysical sensors are located in a distributed manner inside a column, called as sensor column. The sensor columns are approximately 20-25 meters long, are buried deep inside the earth and the data from them are retrieved using lower layer wireless sensor nodes (Crossbows MicaZ motes or WINSOC nodes) attached to the sensor columns. The lower layer wireless sensor nodes are wirelessly connected to a hierarchy of upper level wireless nodes that forward the data on to a Gateway. The data is then sent via a directional Wi-Fi link to a Field Data Management Center (FMC). The data is then forwarded over a satellite link to Data Management Center (DMC) which has sophisticated landslide data processing and modeling capability, located at Amrita University, Amritapuri campus situated approximately 252 kilometers away from the deployment field.
The pilot deployment of the landslide detection system is in place from March 2008. The expanded deployment is in place from June 2009. This new deployment has 15 wireless sensor nodes and a total of 50 geophysical sensors. The real-time data from the deployment field is streamed to the website.
AMRITA wireless sensor network system for landslide detection has been developed as part of the research project WINSOC ( Wireless Sensor Networks with Self-Organization Capabilities for Critical and Emergency Applications) which is co-funded by INFSO DG of European Commission. Further details about the project can be seen in the website.
AMRITA Landslide Laboratory Set Up
Landslide laboratory setups have been created at Amrita for cooperative use with the wireless sensor network deployment in detecting and predicting landslides. This landslide setup has two main purposes:
Provide a test bed for developing, testing, and calibrating the sensors and subsystems of the wireless sensor network
Performing geophysical tests to better understand the nature of landslides, in particular with the soil from the Landslide Wireless Sensor Network Deployment Site. This will give crucial information for assessing the risk of landslide at the deployment site, using the data transmitted from the site.
Two main lab setups, called the medium scale and large scale landslide laboratory setup, have been created for landslide modeling and simulation in the WINSOC project. The small setup served both as a simple, easy to use test setup, as well as a development model for certain aspects of the medium scale landslide setup.
The same sensors as used in the field deployment are also used in the laboratory setups, with an emphasis placed on the pore water pressure meters and dielectric moisture sensors. The sensors used in the laboratory set up collects the changing soil hydrology information at the different areas and depths in the test setup at different times. This information can then be input into the mathematical landslide simulation models for the hydrology inputs.
The experiments conducted in the laboratory set ups will provide key information regarding the behavior of the slope at Idukki under various hydrology and stability conditions and the properties of the soil at the deployment site, as well as increased understanding of how landslides occur with this soil type. Using these laboratory results, based on physical measurements in Munnar, combined with geophysical landslide thresholds derived from earlier experiments, warnings to the local inhabitants could be given via the remote warning system.
Indigenously Designed and Developed, Medium Scale Landslide Laboratory Setups
The medium lab setup measures two meters long by one meter wide by 0.5 meters tall and holds around 0.6 meters3 of soil. It has two main modes of testing. In the first, the soil is packed into the lab setup along with the associated sensors for the experiment. Water is then added in the form of rainfall or seepage, until the slope fails (provided conditions were sufficient for slope failure). In the second type of test, the soil will be saturated to a predetermined level and the entire assembly will be slowly tilted. The angle at which the slope fails will be used to determine many characteristics of the soil at that hydrology state, such as cohesion, friction angle, and others.
Indigenously Designed and Developed, Large Scale Laboratory Set Up for Landslide Detection
The large scale landslide laboratory setup operates in a similar manner as of medium scale laboratory set up, except on a much larger scale. This setup measures 4.6 meters long by 2.6 meters wide by 2 meters tall and is designed to hold approximately 12 cubic meters of soil. In this setup, up to 24 tonne’s of soil can be tested, at a maximum depth of up to 4 feet. Here, the soil can be tested in more lifelike conditions with an increased distance between the slip plane and the boundaries of the lab setup. Similar seepage and rainfall simulators as developed for the medium lab setup are also implemented here. There are again two modes of testing, one for static slopes in which seepage and rainfall flow is added, and the second for relatively static hydrology conditions and a variable tilt.
Small Scale Demonstrator for Forest Fire Detection
CCSS implemented a computer simulator that emulates the spread of a fire through a forest. The simulator also mimics a sensor network designed to monitor and alert of forest fires. Sensors have been placed in a forest in the Czech Republic to detect and locate sources of heat and smoke.
WINSOC Kick-off Meeting
The WINSOC kick-off meeting was held on 14-15 September 2006 in Rome at Selex Communications headquarters. In these two days of meetings, project partners discussed the work packages as well as reporting activities and deliverable review strategies. The EC Officer opened the sessions explaining different issues related to contract and financial matters, including how to prepare audit certificates and how to tackle reports and review processes. Further, the partners decided the composition of the Steering Committee which has been reported in the Project Quality Plan – the first deliverable. Following this, the project was presented by the different participants engaged; the presentation included an overview of project scientific & technological background and foundations, work package descriptions, manpower and finance, as well as the partners profiles and their role in the project. Further exchange of information on landslides and fire detection requirements was agreed between both partners CCSS – Czech Centrum for Science and Society and Amrita University (India). Finally, the next steps and immediate actions were decided, including the completion of the first deliverable – the Project Quality Plan, designing a logo and building the project website. The next meeting will be held in Lausanne – Switzerland, at the EPFL – Ecole Polytechnique Fédérale de Lausanne, by mid January 2007.
Internal Review Meetings
Annual Review Meeting
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Acronym |
WINSOC
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Title of the Project |
WIreless Sensor Networks with Self-Organization Capabilities for Critical and Emergency Applications.
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Contract Number |
33914
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Start date – End date |
01/ 09 / 2006 – 28 / 02 / 2009
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Duraion (in Months) |
30
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Total Budget |
3.864.552 €
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Total Manpower (pm) |
530
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EC Financial Contribution |
2.443.856 €
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Partners |
11 Partners
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Countries |
7 Countries
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Project Coordinator |
Paolo CAPODIECI
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Scientific Coordinator |
Sergio BARBAROSSA
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Financial Coordinator |
Anna RONCONE
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Program Manager |
Paolo Del CARRATORE
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Website |
| Deliverable No |
Deliverable Title | Delivery Date |
Nature5 | Dissemination Level6 |
|---|---|---|---|---|
| D1.1 | Project Quality Plan | 1 | R | PU |
| D1.2 | Final Project Report (M30) | 30 | R | PU |
| D2.1 | Sensor Network Scenarios, Services and Requirements on Sensor Network | 6 | R | PU |
| D2.2 | Components for Sensor Nodes and Transducers | 12 | R | PU |
| D3.1 | Intermediate Report on Algorithms Development | 6 | R | PU |
| D3.2 | Final Report on Algorithms Development | 15 | R | PU |
| D4.1 | Architecture of WINSOC Simulators | 20 | R | PU |
| D4.1.1 | System Level Simulator | 20 | P | CO |
| D4.1.2 | Network Level Simulator | 20 | P | CO |
| D4.1.3 | Node Level Simulator | 16 | P | CO |
| D4.2 | Report on the Analysis of Modulation Techniques and Radio Technologies | 12 | R | PU |
| D4.3 | Report on the Information Extraction Methodologies | 14 | R | PU |
| D4.4 | System level Network Performance Evaluation | 18 | R | PU |
| D4.5 | Specifications of the Sensor Node Prototype | 20 | R | PU |
| D5.1 | Report on Power Supply Solutions | 15 | PU | |
| D5.2 | Performance Evaluation of Miniature Antenna Technologies | 20 | R | PU |
| D5.3 | Validation of the Sensor Node Prototype | 26 | R | PU |
| D5.4 | Validated Sensor Node Prototype (hardware/firmware) | 26 | P | CO |
| D6.1 | Pre-deployment Analysis | 23 | R | PU |
| D6.2 | Proof of Concept Results and Recommendations | 30 | R | PU |
| D6.3 | Small Scale Demonstrator for Fire Detection | 30 | D | CO |
| D7.1 | Dissemination and Exploitation: Intermediate Report | 18 | R | PU |
| D7.2 | Dissemination and Exploitation: Final Report | 30 | R | PU |
| D7.3 | Business Analysis | 30 | R | PU |
| D8.1 | Validation and Impact Assessment: Intermediate Report | 18 | R | PU |
| D8.2 | Validation and Impact Assessment: Final Report | 30 | R | PU |
| D8.2 | Socio Economic Impact Report | 30 | R | PU |
| D8.4 | Performance Evaluation and Deployment Issues for Application of Sensor Networks to Landslide Management | 30 | R | PU |
| 5 Nature of the deliverable is using one of the following codes:
R = Report
P = Prototype D = Demonstrator O = Other 6 Dissemination level is using one of the following codes: PU = Public
PP = Restricted to other program participants (including the Commission Services). RE = Restricted to a group specified by the consortium (including the Commission Services). CO = Confidential, only for members of the consortium (including the Commission Services). |
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| Leonidas Georgopoulosy , Martin Haslery, Nonlinear Average Consensus | A.Khadivi, L.Georgopoulos, and M.Hasler, Forest fire localization using distributed algorithms in wireless sensor networks |
| Maneesha V. Ramesh, K. P. Soman, Wireless Sensor Network Localization With Imprecise Measurements Using Only a Quadratic Solver | Maneesha V. Ramesh, Sangeeth Kumar, and P. Venkat Rangan, Wireless Sensor Network for Landslide Detection |
| M.V. Ramesh, N. Vasudevan, and J. Freeman, Real Time Landslide Monitoring via Wireless Sensor Network, Proceedings of the Geophysical Research Abstracts, Vol. 11, EGU2009-14061, 2009’EGU General Assembly 2009. | Maneesha V. Ramesh, Real-time Wireless Sensor Network for Landslide Detection, Proceedings of the 2009 Third International Conference on Sensor Technologies and Applications,July 2009 . |
| Rehna Raj ,Maneesha V. Ramesh, and Sangeeth Kumar, Fault Tolerant Clustering Approaches in Wireless Sensor Network for Landslide Area Monitoring, Proceeding of the 2008 International Conference on Wireless Networks (ICWN’08), Vol. 1, Pages. 107–113, CSREA Press, July, 2008. | Maneesha V. Ramesh, and P. Ushakumari, Threshold Based Data Aggregation Algorithm To Detect Rainfall Induced Landslides, Proceedings of the 2008 International Conference on Wireless Networks (ICWN08), Vol. 1, Pages. 255261, CSREA Press, July, 2008. |
| J. Freeman, M. V. Remesh, A. Mohan, Biologically Inspired Data Propagation and Aggregation Method, Proceedings of 2008 International Conference on Wireless Networks (ICWN’08), Vol. 1, Page. 255-261, CSREA Press, July 2008. | S. Barbarossa, G. Scutari, T. Battisti, Cooperative sensing for cognitive radio using decentralized projection algorithms, IEEE 10th Workshop on Signal Processing Advances in Wireless Communications, June 2009. |
| S. Sardellitti, S. Barbarossa, L. Pezzolo, Distributed double threshold spatial detection algorithms in wireless sensor networks”, IEEE 10th Workshop on Signal Processing Advances in Wireless Communications, June 2009. | S. Barbarossa, G. Scutari, T. Battisti, Distributed signal subspace projection algorithms with maximum convergence rate for sensor networks with topological constraints, IEEE International Conference on Acoustics, Speech and Signal Processing, April 2009. |
| L. Georgopoulos, M.Hasler, Early Consensus in Complex Networks under Variable Graph Topology, Accepted for publication in the Proceedings of the European Conference on Circuit Theory and Design (ECCTD 2009), Antalya, Turkey, Aug, 2009. | A. Khadivi, M.Hasler, Fire Detection and Localization Using Wireless Sensor Networks, Accepted for publication in the Proceedings of the 1st International Conference on Sensor Networks Applications, Experimentation and Logistics, Athens, Greece, September 2009. |
| G. Scutari, S. Barbarossa, Distributed Consensus Over Wireless Sensor Networks Affected by Multipath Fading, IEEE Transactions on Signal Processing, Vol. 56, Issue 8, Aug. 2008. | G. Scutari, S. Barbarossa, L. Pescosolido, Distributed Decision Through Self-Synchronizing Sensor Networks in the Presence of Propagation Delays and Asymmetric Channels, IEEE Transactions on Signal Processing, Vol. 56, April 2008. |
| L. Pescosolido, S. Barbarossa, G. Scutari, IEEE Radar Conference, 2008, 26-30 May 2008. | L. Pescosolido, S. Barbarossa, G. Scutari, Average consensus algorithms robust against channel noise, IEEE 9th Workshop on Signal Processing Advances in Wireless Communications, July 2008. |
| S. Sardellitti, M. Giona, S. Barbarossa, Fast distributed consensus algorithms based on advection-diffusion processes, 5th IEEE Sensor Array and Multichannel Signal Processing Workshop, July 2008. | P. Di Lorenzo, S. Barbarossa, Wireless Sensor Networks with Distributed Decision Capabilities Based on Self Synchronization of Relaxation Oscillators, International Wireless Communications and Mobile Computing Conference, Aug. 2008. |
| P. Di Lorenzo, S. Barbarossa, Wireless Sensor Networks with Distributed Decision Capabilities Based on Self Synchronization of Relaxation Oscillators, International Wireless Communications and Mobile Computing Conference, Aug. 2008. | S. Barbarossa, T. Battisti, L. Pescosolido, S. Sardellitti, G. Scutari, Distributed Processing Algorithms for Wireless Sensor Networks Having Fast Convergence and Robustness Against Coupling Noise, IEEE 10th International Symposium on Spread Spectrum Techniques and Applications, Aug. 2008. |
| S. Barbarossa, T. Battisti, A. Swami, Globally optimal decentralized spatial smoothing for wireless sensor networks with local interactions, IEEE International Conference on Acoustics, Speech and Signal Processing, April 4 2008. | L. Pescosolido, S. Barbarossa, Distributed decision in sensor networks based on local coupling through Pulse Position Modulated signals, IEEE International Conference on Acoustics, Speech and Signal Processing, April 2008. |
| Silva Pereira S. and Pages-Zamora A, Distirbuted Consensus in Wireless Sensor Networks with Quantized Information Exchange, Proceedings of the 9th IEEE International Workshop on Signal Processing Advances in Wireless Communications, (SPAWC), 5 pages, Recife, Brazil, July 06 – 09, 2008. | Maneesha V. Ramesh, Rehna Raj, Joshua Udar Freeman, Sangeeth Kumar, and P. Venkat Rangan, Factors and Approaches for Energy Optimized Wireless Sensor Network to Detect Rainfall Induced Landslides, Proceedings of the 2007 International Conference on Wireless Networks (ICWN’07), Pages. 435-438, CSREA Press, June 2007. |
| G. Scutari, S. Barbarossa, L. Pescosolido, Distributed decision through self-synchronizing sensor networks in the presence of propagation delays and nonreciprocal channels, Proceedings of SPAWC 2007, Helsinki, Finland, June 2007. | P. Closas, E. Calvo, J. A. Fernández-Rubio, A. Pages-Zamora, Coupling Noise Effect in Self-Synchronizing Wireless Sensor Networks, Proceedings of the IEEE Signal Processing Workshop on Signal Processing Advances in Wireless Communications (SPAWC), 5 pages, Helsinki, Finland, June 17-20, 2007. |
| S. Barbarossa, G. Scutari, A. Swami, Achieving consensus in self-organizing wireless sensor networks: The impact of network topology on energy consumption, Proceedings of IEEE International Conference on Acoustics, Speech and Signal Proceedings, ICASSP 2007, Honolulu, Hawaii, April 2007. | Sergio Barbarossa and Gesualdo Scutari, Bio-Inspired Sensor Network Design – Distributed decisions through self-synchronization |
| Sergio Barbarossa, Gesualdo Scutari, Decentralized Maximum Likelihood Estimation for Sensor Networks Composed of Nonlinearly Coupled Dynamical Systems, publication on the IEEE Transactions on Signal Processing. | Sensor based Landslide Early Warning System – SLEWS |
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WINSOC,
Amrita Center for Wireless Networks and Applications,
Amrita Vishwa Vidyapeetham,
Amritapuri Campus,
Kollam – 690525.
Telephone: +91 476 2801280
Fax: +91 476 2896178