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НИЛ АСЭМ Научно - исследовательская лаборатория автоматизированных систем экологического мониторинга

Экологический мониторинг

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51. Larios D.F., Barbancho J., Sevillano J.L., Rodríguez G., Molina F.J., Gasull V.G., Mora-Merchan J.M. and León C. Five Years of Designing Wireless Sensor Networks in the Doñana Biological Reserve (Spain): An Applications Approach // Sensors. - 2013, V.13, P. 12044-12069; doi:10.3390/s130912044.

Abstract: Wireless Sensor Networks (WSNs) are a technology that is becoming very popular for many applications, and environmental monitoring is one of its most important application areas. This technology solves the lack of flexibility of wired sensor installations and, at the same time, reduces the deployment costs. To demonstrate the advantages of WSN technology, for the last five years we have been deploying some prototypes in the Doñana Biological Reserve, which is an important protected area in Southern Spain. These prototypes not only evaluate the technology, but also solve some of the monitoring problems that have been raised by biologists working in Doñana. This paper presents a review of the work that has been developed during these five years. Here, we demonstrate the enormous potential of using machine learning in wireless sensor networks for environmental and animal monitoring because this approach increases the amount of useful information and reduces the effort that is required by biologists in an environmental monitoring task.

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References
1. Chong, C.-Y.; Kumar, S. Sensor Networks: Evolution, Opportunities, and Challenges. Proc. IEEE 2003, 91, 1247–1256.
2. Akyildiz, I.; Su, W.; Sankarasubramaniam, Y.; Cayirci, E. A Survey on Sensor Networks. IEEE Commun. Mag. 2002, 40, 102–114.
3. Ruiz-Garcia, L.; Lunadei, L.; Barreiro, P.; Robla, I. A review of wireless sensor technologies and applications in agriculture and food industry: State of the art and current trends. Sensors 2009, 9, 4728–4750.
4. Kumagai, J. Life of birds [wireless sensor network for bird study]. IEEE Spectr. 2004, 41, 42–49.
5. Machado, R.; Ansari, N.; Wang, G. Tekinay, S. Adaptive density control in heterogeneous wireless sensor networks with and without power management. IET Commun. 2010, 4, 758–767.
6. Batista, N.; Melicio, R.; Matias, J. Catalao, J. ZigBee Standard in the Creation of Wireless Networks for Advanced Metering Infrastructures. In Proceedings of 16th IEEE Mediterranean Electrotechnical Conference (MELECON), Yasmine Hammamet, Tunisia, 25–28 March 2012; pp. 220–223.
7. Pantazis, N.; Nikolidakis, S.; Vergados, D. Energy-Efficient Routing Protocols in Wireless Sensor Networks: A Survey. IEEE Commun. Surv. Tutor. 2013, 15, 551–591.
8. Haneef, M.; Zhongliang, D. Design challenges and comparative analysis of cluster based routing protocols used in wireless sensor networks for improving network life time. Adv. Inf. Sci. Serv. Sci. 2012, 4, 450–459.
9. Liu, L.; Wu, C. A novel power intensity routing in wsn. Int. J. Digit. Content Technol. Appl. 2012, 6, 178–184.
10. Ding, D.; Liu, F.; Li, Q.; Yang G. An improved clustering algorithm based on backup path. Adv. Inf. Sci. Serv. Sci. 2012, 4, 207–216.
11. Shen, Z..; Liu, S. Security threats and security policy in wireless sensor networks. Adv. Inf. Sci. Serv. Sci. 2012, 4, 166–173.
12. Fenhua, C. A distributed dynamic pairwise key establishment scheme for wireless sensor networks. Int. J. Adv. Comput. Technol. 2012, 4, 261–267.
13. Li, H.; Pang, L.; Wang, Y. A domain-based secure communication scheme with fault-tolerant capacity. Adv. Inf. Sci. Serv. Sci. 2012, 4, 44–52.
14. Barbancho, J.; Leon, C.; Cantero, F.J.M.; Barbancho, A. New Qos Routing Algorithm Based on Self-Organizing Maps for Wireless Sensor Networks. Telecommun. Syst. 2007, 36, 73–83.
15. Larios, D.F.; Barbancho, J.; Rodriguez, G.; Sevillano, J.F.; Molina, J.; Leon, C. Energy efficient wireless sensor network communications based on computational intelligent data fusion for environmental monitoring. IET Commun. 2012, 6, 2189–2197.
16. Larios, D.; Barbancho, J.; Molina, F.; Leon, C. LIS: Localization based on an intelligent distributed fuzzy system applied to a WSN. Ad Hoc Netw. 2012, 10, 604–622.
17. Deng, B.; Wuhan, C.; Huang, G.; Zhang, L.; Liu, H. Improved Centroid Localization Algorithm in WSNs. In Proceedings of the 3rd International Conference on Intelligent System and Knowledge Engineering (ISKE), Xiamen, China, 17–19 November 2008; pp. 1260–1264.
18. Gasull, V.G.; Larios, D.F.; Barbancho, J.; Leon, C.; Obaidat, M.S. A Wildfire prediction based on fuzzy inference system for wireless sensor networks. e-Bus. Telecommun. 2012, 314, 43–59.
19. Gasull, V.G.; Larios, D.F.; Barbancho, J.; Leon, C.; Obaidat, M.S. Computational Intelligence Applied to Wildfire Prediction using Wireless Sensor Network. In Proceedings of the 8th International Joint Conference on e-Business and Telecommunications, Seville, Spain, 18–21 July 2011; pp. 14–21.
20. Heinsch, F.A.; Andrews, P.L. BehavePlus Fire Modeling System, Version 5.0: Design and Features; USDA Forest Service: Fort Collins, CO, USA, 2010.
21. Bijleveld, M. Birds of Prey in Europe, 1st ed.; Eds.: Seeger, I.; Publisher: Macmillan, London, UK, 1974; pp. 1–288.
22. Garzon, J. Birds of Prey in Spain, the Present Situation. In Proceedings of the World Conference on Birds of Prey, Vienna, Austria, 1–3 October 1975; pp. 159–170.
23. Biber, J.P. Action Plan for the Conservation of Western Lesser Kestrel Falco Naumanni Populations, 1st ed.; ICBP Secretariat; Publisher: Cambridge, UK, 1990; pp. 1–46.
24. González, J.; Merino, M. El Cernicalo Primilla (Falco Naumanni) En La Peninsula Iberica: Situacion, Problematica Y Aspectos Biologicos (Spanish Edition), 1st ed.; ICONA: Madrid, Spain, 1990; pp. 1–119.
25. Peet, N.; Gallo-Orsi, U. Action Plan for the Lesser Kestrel, 1st ed.; Council of Europe and BirdLife International, Publisher: Cambridge, London, UK, 2000; pp. 1–42.
26. Newton, I. Lifetime Reproduction in Birds; Academic Press: London, UK, 1992.
27. Trivers, R. Parent-offspring conflict. Integr. Comp. Biol. 1974, 14, 249–264.
28. Schlomer, G.; Ellis, B.; Garber, J. Mother–child conflict and sibling relatedness: A test of hypotheses from parent-offspring conflict theory. J. Res. Adolesc. 2010, 20, 287–306.
29. Smith, J.M.; Price, G. The logic of animal conflict. Nature 1973, 246, 15–18.
30. Kokko, H.; Wong, B. What determines sex roles in mate searching? Evolution 2007, 61, 1162–1175.
31. Larios, D.; Rodríguez, C.; Barbancho, J.; Baena, M.; Leal, M.; Marin, J.; Leon, C.; Bustamante, J. An automatic weighting system for wild animals based in an artificial neural network: How to weigh wild animals without causing stress. Sensors 2013, 13, 2862–2883.
32. Green, A. Mass/Length residuals: Measures of body condition or generators of spurious results? Ecology 2001, 82, 1473–1483.
33. Biebach, H.; Friedrich, W.; Heine, G. Interaction of bodymass, fat, foraging and stopover period in trans-sahara migrating passerine birds. Oecologia 1986, 69, 370–379.
34. Hill, G. Female house finches prefer colourful males: Sexual selection for a condition-dependent trait. Anim. Behav. 1990, 40, 563–572.
35. Lumeij, J.; Remple, J. Plasma urea, creatinine and uric acid concentrations in relation to feeding in peregrine falcons (Falco peregrinus). Avian Pathol. 1991, 20, 79–83.
36. Larios, D.F.; Rodriguez, C.; Barbancho, J.; Baena, M.; Simon, F.; Marin, J.; Leon, C.; Bustamante, J. Computational Intelligence Applied to Monitor Bird Behaviour. In Proceedings of the 9th International Joint Conference on e-Business and Telecommunications, Rome, Italy, 24–27 July 2012; pp. 23–32.
37. Fernandez, N.; Paruelo, J.; Delibes, M. Ecosystem functioning of protected and altered Mediterranean environments: A remote sensing classification in Doñana, Spain. Remote Sens. Environ. 2010, 114, 211–220.
38. Kandris, D.; Tsagkaropoulos, M.; Politis, I.; Tzes, A.; Kotsopoulos, S. Energy efficient and perceived QoS aware video routing over wireless multimedia sensor networks. Ad Hoc Netw. 2011, 9, 591–607.
39. Ko, J.; Terzis, A.; Dawson-Haggerty, S.; Culler, D.; Hui, J.; Levis, P. Connecting low-power and lossy networks to the internet. IEEE Commun. Mag. 2011, 49, 96–101.
40. Hong, S.; Kim, D.; Ha, M.; Bae, S.; Park, S.J.; Jung, W.; Kim, J.-E. SNAIL: An IP-based wireless sensor network approach to the internet of things. IEEE Wirel. Commun. 2010, 17, 34–42.
41. Dinh, N.-T.; Kim, Y. Restful architecture of wireless sensor network for building management system. Trans. Internet Inf. Syst. 2012, 6, 46–63.
42. Jara, A.; Fernndez, D.; Lopez, P.; Zamora, M.; Marin, L.; Skarmeta, A. Yoapy: A data aggregation and pre-processing module for enabling continuous healthcare monitoring in the internet of things. Lect. Note Comput. Sci. 2012, 7657, 248–255.
43. Ha, M.; Kim, S.-H.; Kim, H.; Kwon, K.; Giang, N.; Kim, D. SNAIL Gateway: Dual-Mode Wireless Access Points for WiFi and IP-Based Wireless Sensor Networks in the Internet of Things. In Proceedings of IEEE Consumer Communications and Networking Conference (CCNC), Las Vegas, NV, USA, 14–17 January 2012; pp. 169–173.
44. Shelby, Z. Embedded web services. IEEE Wirel. Commun. 2010, 17, 52–57.
45. Rajasekaran, P.; Janardhan, R.; Chander, R. A Smarter Toll Gate Based on Web of Things. In Proceedings of IEEE International Conference on Electronics, Computing and Communication Technologies (CONECCT), Bangalore, India, 17–19 January 2013; pp. 1–6.
46. Wang, Y.; Qian, Z.; Wang, X.; Sun, D. Addressing scheme for internet of things based on IPv6 over low-power wireless personal area network (6loWPAN). J. Electron. Inf. Technol. 2012, 34, 763–769.
47. Yu, H.; He, J. Trust-based mutual authentication for bootstrapping in 6lowpan. J. Commun. 2012, 7, 634–642.
48. Oliveira, L.; Rodrigues, J.; Sousa, A.D.; Lloret, J. Denial of service mitigation approach for IPv6-enabled smart object networks. Concurr. Comput. Pract. Exp. 2013, 25, 129–142.
49. Lu, R.; Wang, X.L.J.; Sun, F. Research on route protocol and architecture for wsn based on IPv6. Adv. Mater. Res. 2013, 1, 616–618.
50. Castellani, A.P.; Rossi, M.; Zorzi, M. Back pressure congestion control for CoAP/6LoWPAN networks. Ad Hoc Netw. 2013, doi:10.1016/j.adhoc.2013.02.007.
51. Bormann, C.; Castellani, A.P.; Shelby, Z. CoAP: An application protocol for billions of tiny internet nodes. IEEE Internet Comput. 2012, 16, 62–67.
52. Somervuo, P.; Univ, H.; Harma, A.; Fagerlund, S. Parametric Representations of Bird Sounds for Automatic Species Recognition. IEEE Trans. Audio Speech Lang. Process. 2006, 14, 2252–2263.
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by Admin » Thu Jan 30, 2020 11:53 am

52. Hwang J., Shin C. and Yoe H. Study on an Agricultural Environment Monitoring Server System using Wireless Sensor Networks // Sensors. - 2010, V.10. P. 11189-11211; doi:10.3390/s101211189.

Abstract: This paper proposes an agricultural environment monitoring server system for monitoring information concerning an outdoors agricultural production environment utilizing Wireless Sensor Network (WSN) technology. The proposed agricultural environment monitoring server system collects environmental and soil information on the outdoors through WSN-based environmental and soil sensors, collects image information through CCTVs, and collects location information using GPS modules. This collected information is converted into a database through the agricultural environment monitoring server consisting of a sensor manager, which manages information collected from the WSN sensors, an image information manager, which manages image information collected from CCTVs, and a GPS manager, which processes location information of the agricultural environment monitoring server system, and provides it to producers. In addition, a solar cell-based power supply is implemented for the server system so that it could be used in agricultural environments with insufficient power infrastructure. This agricultural environment monitoring server system could even monitor the environmental information on the outdoors remotely, and it could be expected that the use of such a system could contribute to increasing crop yields and improving quality in the agricultural field by supporting the decision making of crop producers through analysis of the collected information.

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References
1. Kim, M.K.; Park, J.H.; Cho, Y.W. Current Trends and Industrial Strategies of IT Convergence; ETRI Electronic Communications Trend Report; Electronics and Telecommunications Research Institute: Daejeon, Korea, February 2010; Volume 25, No. 1.
2. Lee, K.H.; Ahn, C.M.; Park, G.M. Characteristics of the Convergence among Traditional Industries and IT Industry; ETRI Electronic Communications Trend Report; Electronics and Telecommunications Research Institute: Daejeon, Korea, April 2008; Volume 23, No. 2.
3. Gim, B.-G.; Lee, W.-J.; Heo, S.-Y. Construction of a Testbed for Ubiquitous Plant Factory Monitoring System Using Artificial Lighting. In Proceedings of Korean Institute of Information Technology, 2010 Summer Conference, Suwon, Korea, May 2010; pp. 272-275.
4. Shin, Y.-S. A Study on Informatization Model for Agriculture in Ubiquitous Era; MKE Research Report; National IT Industry Promotion Agency: Seoul, Korea, 2006. 5. Park, D.-H.; Kang, B.-J.; Cho, K.-R.; Sin, C.-S.; Cho, S.-E.; Park, J.-W.; Yang, W.-M. A Study on Greenhouse Automatic Control System Based on Wireless Sensor Network. Wireless Pers Commun. 2009, doi: 10.1007/s11277-009-9881-2.
6. Jeong, B.-M. Foreign u-Farm Service Model Casebook; Issues and Analysis Report of Korea National Information Society Agency, NCA V–RER-06005; Korea National Information Society Agency: Seoul, Korea, October 2006.
7. Kwon, O-B.; Kim, J.-H. A Basic Direction for Building Agricultural Radio Frequency Identification Logistics Information System; Research Report M85; Korea Rural Economics Institute: Seoul, Korea, December 2007.
8. Lee, M.-H.; Shin, C.-S.; Jo, Y.-Y.; Yoe, H. Implementation of Green House Integrated Management System in Ubiquitous Agricultural Environments. J. KIISE 2009, 27, 21-26.
9. Yoo, N.; Song, G.; Yoo, J.; Yang, S.; Son, C. Koh, J.; Kim, W. Design and Implementation of the Management System of Cultivation and Tracking for Agricultural Products using USN. J. KIISE 2009, 15, 617-674.
10. UDFC ALERT System Real-Time Flood Detection & Current Weather Conditions; Available online: http://alert.udfcd.org (accessed on 3 December 2010).
11. Pierce, F.J.; Elliott, T.V. Regional and on-Farm Wireless Sensor Networks for Agricultural Systems in Eastern Washington. Comput. Electron. Agric. 2008, 61, 32-43.
12. Ayday, C.; Safak, S. Application of Wireless Sensor Networks with GIS on the Soil Moisture Distribution Mapping. In Proceedings of Symposium GIS Ostrava 2009—Seamless Geoinformation Technologies, Ostrava, Czech Republic, 25–28 January 2009.
13. Han, W.; Zhang, N.; Zhang, Y. A two-layer Wireless Sensor Network for Remote Sediment Monitoring. In Proceedings of 2008 ASABE Annual International Meeting, Rhode Island, RI, USA, 29 June–July 2008.
14. Hamrita, T.K.; Hoffacker, E.C. Development of a "Smart" Wireless soil Monitoring Sensor Prototype Using RFID Technology. Appl. Eng. Agric. 2005, 21, 139-143.
15. USC Precision Agriculture; Available online: http://www.gpoaccess.gov/uscode/index.html (accessed on 3 December 2010).
16. Baggio, A. Wireless Sensor Networks in Precision Agriculture. In Proceeding of Workshop on Real-World Wireless Sensor Networks. REALWSN'05, Stockholm, Sweden, 20–21 June 2005.
17. Burrell, J.; Brooke, T.; Beckwith, R. Vineyard Computing: Sensors Networks in Agricultural Production. Lect. Note. Comput. Sci. 2004, 3, 38-45.
18. Beckwith, R.; Teibel, D.; Bowen, P. Report from the Field: Results from an Agricultural Wireless Sensor Network. In Proceeding of 29th Annual IEEE International Conference on Local Computer Networks, Tampa, FL, USA, 16–18 November 2004.
19. Morais, R.; Fernandes, M.A.; Matos, S.G.; Serodio, C.; Ferreira, P.; Reis, M. A ZigBee Multipowered Wireless Acquisition Device for Remote Sensing Applications in Precision Viticulture. Comput. Electron. Agric. 2008, 62, 94-106.
20. Liu, G.; Ying, Y. Application of Bluetooth Technology in Greenhouse Environment, Monitor and Control. J. Zhejiang Univ. Agric. Life Sci. 2003, 29, 329-334.
21. Gonda, L.; Cugnasca, C.E. A Proposal of Greenhouse Control Using Wireless Sensor Networks. In Proceedings of Computers in Agriculture and Natural Resources, 4th World Congress Conference, Orlando, FL, USA, 24–26 July 2006.
22. Yoo, S.; Kim, J.; Kim, T.; Ahn, S.; Sung, J.; Kim, D. A2S: Automated Agriculture System Based on WSN. In Proceedings of ISCE 2007. IEEE International Symposium on Consumer Electronics, Irving, TX, USA, 20–23 June 2007.
23. Lea-Cox, J.D.; Kantor, G.; Anhalt, J.; Ristvey, A.; Ross, D.S. A Wireless Sensor Network for the Nursery and Greenhouse Industry. In Proceedings of Southern Nursery Association Research Conference, Atlanta, GA, USA, 8–9 August 2007; Volume 52.
24. Liu, H.; Meng, Z.; Cui, S. A Wireless Sensor Network Prototype for Environmental Monitoring in Greenhouses. In Proceedings of International Conference on Wireless Communications, Networking and Mobile Computing (WiCom 2007), Shangai, China, 21–25 September 2007.
25. Zhou, Y.M.; Yang, X.L.; Guo, X.S.; Zhou, M.G.; Wang, L.R. A Design of Greenhouse Monitoring & Control System Based on ZigBee Wireless Sensor Network. In Proceedings of 2007 International Conference on Wireless Communications, Networking and Mobile Computing (WiCom 2007), Shangai, China, 21–25 September 2007.
26. Yang, I.-C.; Chen, S.; Huang, Y.-I.; Hsieh, K.-W.; Chen, C.-T.; Lu, H.-C.; Chang, C.-L.; Lin, H.-M.; Chen, Y.-L.; Chen, C.-C.; Lo, Y.M. RFID-Integrated Multi-Functional Remote Sensing System for Seedling Production Management. In Proceedings of 2008 ASABE Annual International Meeting, Providence, RI, USA, 29 June 2008.
27. MSP430 Mixed Signal Microcontroller; Available online: http://www.alldatasheet.co.kr (accessed on 6 September 2010). 28. CC2420 2.4 GHz IEEE 802.15.4 / Zigbee RF Transceiver; Available online: http://www.alldatasheet.co.kr (accessed on 6 September 2010).


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