It is currently Wed Oct 17, 2018 3:34 am

НИЛ АСЭМ Научно - исследовательская лаборатория автоматизированных систем экологического мониторинга

Экологический мониторинг

Подборка научных статей

by Admin » Tue Apr 03, 2018 1:53 pm

11. Balaji R., Ganesan R. Remote Water Pollution Monitoring System Using GSM // Proc. of the Intl. Conf. on Advances in Computer, Electronics and Electrical Engineering Editor In Chief Dr. R. K. Singh. Copyright © 2012 Universal Association of Computer and Electronics Engineers.

Abstract: Water pollution is one of the key threats for the green globalization. To prevent the water pollution, first we have to detect the pollutant. In earlier days, the water pollution was detected by chemical test or laboratory test by using this system the testing equipment will be in stationary and samples will be given to testing equipment. In order to increase the pervasiveness, testing equipment can be placed in the river water and detection of pollution can be made remotely. This paper proposes a Sensor-Based Water Pollution Detection, which will detect the pollutant present in the water and give an alert massage to the agent. The sensor pH, turbidity and DO will be kept in the river water surface and the data captured by the sensor will be given to PIC Microcontroller, and then the data are transmitted wirelessly using Zigbee module. After calculating the inference from the sensed data, In case of inference value above the threshold value automated warning SMS alert will be sent to the agent. As an additional feature this sensors will be auto powered by Wind based piezoelectric material. The uniqueness of our proposed paper is to obtain the water monitoring system with high pervasiveness, high mobility, and low powered.


Main Figures:
Image


References
[1] ManJing, Weifang, ShanDong, “The design of wireless remote
monitoring system of water supply based on GPRS” International
Symposium on Computer Science and Society 2011

[2] Ruan Yue, Tang Ying, Hangzhou, Zhejiang Province,” A water
quality monitoring system based on wireless sensor network & solar
power supply” Proceedings of the 2011 IEEE International
Conference on Cyber Technology in Automation, Control, and
Intelligent Systems March 20-23, 2011

[3] Nusrat Sharmin Islam and Md. Wasi-ur-Rahman,” An Intelligent
SMS-Based Remote Water Metering System” Proceedings of 2009
12th International Conference on Computer and Information
Technology (ICCIT 2009) 21-23 December, 2009

[4] Alex Anvari, Jenny Delos Reyes, Ehsan Esmaeilzadeh, Ali
Jarvandi, Nicholas Langley, Keyssi Rivera Navia, “Designing an
Automated Water Quality Monitoring System for West and Rhode
Rivers” IEEE Systems and Information Engineering Design
Symposium, University of Virginia, Charlottesville, VA, USA, IEEE,
2009

[5] Fiona Regan, Antoin Lawlor, ”A demonstration of wireless
sensing for long term monitoring of water quality”, International
Workshop on Practical Issues In Building Sensor Network
Applications, National Centre for Sensor Research, Dublin City
University, Glasnevin, IEEE, 2009

[6] Brad Garner, ,”New Sensor Technologies for Real-Time Water
Quality Monitoring”, Hydrologist US Geological Survey, MD-DEDC
Water Science Center, IEEE, 2007

[7] Tong-Won Kwon,Yong-Man Park,Sang-Jun,Koo,Hiesik Kim,
”Design of Air Pollution Monitoring System using Zigbee Networks
for Ubiquitous-City”, International Conference on Convergence
Information Technology, IEEE, 2007

[8] Deng yu,wang juan “Application of Remote Sensing Monitoring
System in the Yellow River” 2nd international conference on signal
processing system(ICSPS)2010

[9]Li pengfei, Li jiakun,jing junfeng” Wireless Temperature
Monitoring System Based on the Zigbee Technology”2nd
International Conference on computer Engineering and Technology 2010.
Admin
Site Admin
 
Posts: 203
Joined: Wed Sep 20, 2017 9:55 am

by Admin » Thu Apr 12, 2018 10:51 am

12. Satish B. Jadhav & Neeta S. Automatic Measurement and Reporting System of Water Quality Based On GSM // Imperial Journal of Interdisciplinary Research (IJIR). – 2016. Vol. 2. Issue-5. P. 657 – 662.

Abstract:Water quality is one of the key threat for green globalization .Due to increase the economic development of Indian we can see the resulting speeding up the contamination and damage .peoples also responsible who throw garbage material in water, due to this water quality will be damaged. The conventional technique of measuring the quality of water is to gather the samples manually and send it to laboratory for analysis, but it has unable to meet demand of water quality today. It is not feasible to take water sample manually for laboratory after every hour for measuring and monitoring water quality .so this paper proposes automatic measurement and reporting system of water quality .The set up consist of PIC microcontroller, water quality sensors, base station, monitoring center and other system. The parameter involved in the water quality determination such as the PH level, DO, Turbidity and Temperature. The water quality system can measuring the required qualities of water in real time .Firstly the total data can send to PIc Microcontroller and process and analyze them. After that the data are sent to monitoring center by GSM in the form of SMS .If water quality is abnormal the data will be sent to monitoring center and management mobile simultaneously at same time .The system has realized , intelligence of data analyzing and networking of information transferring.

Main Figures:

Image
Structure

ImageImage
System

References
[1] Zulhani Rasin and Mohd Rizal Abdullah-“Water quality monitoring system using Zigbee based wireless sensor network” International Journal of Engineering and Technology IJIET-IJENS vol :09 No :10.
[2]Mo Deqing, Zhao ying,Chen Shangsong-“Automatic Measurement and Reporting System of Water Quality based on GSM” International Conference on Intelligent System Design and Engineering Application 2012.
[3] Yazeed Al-Obaisat, Robin Braun Institute of Information and Communication Technologies “ On Wireless Sensor Networks: Architectures, Protocols, Applications and Management .”
[4]Wael Hosny Faouad Aly-“Wireless Sensor Network for Water Management that supports Differentiated Services”International Journal of Scientific and Engineering Research 2013.
[5] Andrew. F. Colombo,Pedro Lee, Bryan. W. Karney-“A selective literature review of transient - beak leak detection methods” Journal of Hydro-environment Research 2009.
[6] Liu Yan, “Analysis of several water quality indicators in industrial effluent,” Applied Science,2009, 6:147.(in Chinese)
[7] Sun Xiaodong, Jing Yunpeng, “Sensors’ application to environmental monitoring,” Measurement and Testing
Technology, 2006, 33(10):38-39. (in Chinese)
Admin
Site Admin
 
Posts: 203
Joined: Wed Sep 20, 2017 9:55 am

by Admin » Fri Apr 13, 2018 3:15 pm

13. Mounika J., Siva N. Water Monitoring System Based on GSM // International Advanced Research Journal in Science, Engineering and Technology. -2016. Vol. 3, Issue 7. P. 233 – 236.

Abstract: The method to check and control water level for irrigation system. The water is a one of the important natural resource and it is an important assets to save the water on the earth. This paper describes the automatic system to monitor and control water level with the help of water level sensors and wireless network system. The need of this paper is to cut water wastage occur in canel and subcanel, and the WSN system reduces the human efforts.

Main Figures:
Image Image

References
[1] Burrell, T. Bro, A. Camilli, C.E. Cugnasca, A.M. Saraiva, A.R. Hirakawa, and P. L. P.CorrAea. From wireless sensors to field mapping: Anatomy of an application for recision agriculture. Comput. Electron.Agric. 58( I ):25-36,2007.

[2] Guangming Song, Fei Ding, Weijuan Zhang and Aiguo Song, “A Wireless Power Outlet System for Smart Homes, "IEEE Transactions on Consumer Electronics, Vol. 54, No.4, November, 2008.

[3] Shen Jin, Song Jingling, Han Qiuyan, Wang Shengde, Yang Yan, "A Remote Measurement and Control System for Greenhouse based on GSM-SMS" IEEE 8th International Conference on Electronic Measurement and Instrument, 2007.

[4] G.K. Banerjee, Rahul Singhal, Bhubaneswar, Orissa India "Microcontroller Based Polyhouse Automation Controller", International Symposium on Electronic System Design, pp.158- 162, Dec 2010.

[5] Wen bin Huang, Guanglong Wang, Jianglei Lu, Fengqi Gao,1ianhui Chen "Research of wireless sensor networks for an intelligent measurement system based on ARM”, International conference on Mechatronics and Automation, pp. 1074 - 1079,20 II

[6] Yuksekkaya,B.;Kayalar,A.A.;Tosun, M.B.; Ozcan, M.K.; A.Z.;"Research of Wireless Sensor Networks for an Intelligent Measurement System Based on ARM", IEEE Transactions on Mechatronics and Automation, Volume: 52, Issue: 3,2006 , pp. 837 – 843

[7] Yiming Zhou, Xianglong Yang, Wang, L., Yibin Ying School of Biosystems Eng. & Food Sci., Zhejiang Univ., Hangzhou, “A Wireless Design of Low-Cost Irrigation System Using ZigBee Technology", IEEE 2009 International Conference on Networks Security, Wireless Communications and Trusted Computing, vol. 1, pp.572 – 575. 2009.

[8] Wenbin Huang, Guanglong Wang, Jianglei Lu, Fengqi Gao, Jianhui Chen “Research of wireless sensor networks for an intelligent measurement system based on ARM”, International conference on.

[9] Li pengfei, Li jiakun,jing junfeng” Wireless Temperature Monitoring System Based on the Zigbee Technology”2nd International Conference on computer Engineering and Technology 2010.

[10] Hu, D. C Language Programming and Development of MSP430; Beihang University Press: Bejing, China, 2003.

[11] Chipcon ASSmartRF ® CC2420 Preliminary Datasheet (rev1.2); Chipcon AS: Olso, Norway, June 9, 2004.

[12] Hong, J.; Zhu, Q.; Xiao, J. Design and Realization of Wireless Sensor Network Gateway Based on ZigBee and GPRS. 2009 2nd International Conference on Information and Computing Science, Manchester, UK, 2009; pp. 196–199.

[13] 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.

[14] Rhee, I.-K.; Lee, J.; Kim, J.; Serpedin, E.; Wu, Y.-C. Clock Synchronization in Wireless Sensor Networks: An Overview. Sensors 2009, 9, 56–85.

[15] Mills, D.L. Internet Time Synchronization: The Network Time Protocol. IEEE Trans. Commun.1991, 39, 1482–1493.

[16] Elson, J.; Girod, L.; Estrin, D. Fine-Grained Network Time Synchronization Using Reference
Admin
Site Admin
 
Posts: 203
Joined: Wed Sep 20, 2017 9:55 am

by Admin » Wed Apr 18, 2018 1:32 pm


Abstract:
This paper proposes a farming environment observing framework for checking data concerning an outside by using Wireless Sensor Network (WSN) innovation. The proposed rural environment observing server framework gathers natural and soil data on the outside through WSNbased ecological and soil sensors. In this paper we are using sensors as soil moisture sensor and temperature sensor.This sensors help the field to control the water level and also temperature .Here we are using wireless sensor network as GSM (global system for mobile communication).

Main Figures:
Image Image
Image

References
1. Beaulah, S.A., Chalabi, Z.S., Randle, D.G., 1998. A
real-time knowledge-based system for intelligent
monitoring in complex,sensor-rich environments.
Comput. Electron. Agric. 21 (1), 53–68.
2. Butler, Z., Corke, P., Peterson, R., Rus, D., 2004.
Virtual fences for controlling cows. In: Proceedings
of the 2004 IEEE International Conference on
Robotics and Automation, New Orleans, LA, USA,
April 26–May 1, pp. 4429–4436.
3. Q.Hao and Z.Song, "The status and development of
the intelligent Automatic meter reading system,"
China Science and Technology Information, no.19,
pp.72, Oct 2005.
4. Wei Xiaolong. Interface technology and examples of
design of system based on MSP430 series single
chip. Beijing: Beijing university of Aeronautics and
Astronautics Press. 2002.
5. Hamoud, G. Chen, R.-L. Bradley, “Risk assessment
of power systems SCADA,” IEEE Power Engineering
Society General Meeting, 2003, Vol.2, Jul. 2003.
6. Study on an Agricultural Environment Monitoring
Server System using Wireless Sensor by
Networks Jeonghwan Hwang, Changsun Shin and
Hyun Yoe *
7. Detection & Current Weather Conditions; Available
online: http://alert.udfcd.org (accessed on 3
December 2010).
8. UDFC ALERT System Real-Time Flood 11. Pierce,
F.J.; Elliott, T.V. Regional and on-Farm Wireless
Sensor Networks for Agricultural Systems in Eastern
Washington. Computer. Electron. Agric. 2008, 61,
32-43.
Admin
Site Admin
 
Posts: 203
Joined: Wed Sep 20, 2017 9:55 am

by Admin » Wed Apr 18, 2018 2:08 pm

15. Moon A.H., Iqbar U., Mohiuddin Bhat G.M. Secured Data Acquisition System for Smart Water Applications using WSN // Indian Journal of Science and Technology. – 2016. Vol. 9(10). P. 1- 11.

Abstract:
Objectives: The paper presents a comprehensive system design and implementation of a prototype for secure data acquisition of water quality parameters in a real time basis using Wireless Sensor Network. Methods/Analysis: The design is based upon under-water sensors for measuring water parameters, interfaced to a Data Acquisition Board attached with a WSN mote. Layered architecture comprising of Mote Tier, Server Tier and a Client Tier has been employed. The system has been developed on TinyOS using TinyECC library and Matlab. Security service to provide data authentication employs a light-weight-key-generation scheme using ECC. A web based application facilitates visualization of sensor data. Findings: Following simulation in Tossim, the data acquisition application was ported to the WSN hardware with security primitives for data authentication. Field trials were carried out at World famous Dal Lake in Srinagar and data related to pH, Conductivity, ORP/Redox, Temperature, Turbidity and Oxidation was accessed remotely through the web application. For the purpose of recording the field location (Longitude and Latitude), a GPS sensor was also integrated to the WSN set-up. The water quality parameters acquired through the Data Acquisition System were correlated with the water quality test reports of standard labs. Energy and computational calculations were carried and benchmarked to ascertain the suitability of the system design considering the resource constraint nature of WSN. The product has the potential of becoming an important constituent of smart water applications as a requirement of smart city. Novelty/Improvement: The field deployable prototype serves as a generic model for monitoring the water quality of any water body like river ,lake , reservoir etc on a real time basis with the novel feature of employing sensor data authentication as a security service.

Main Figures:
Image

Image

References
1. Kim DH, Suh J, Park KH. An empirical investigation on the
determinants of smart water grid adoption. Indian Journal
of Science and Technology. 2015; 1–9.
2. Wooseung J, Kim TH, Choi K, Kang NG. Leakage Pattern
Monitoring Method of CEP based Water Supply Block System.
Indian Journal of Science and Technology. 2015 Oct;
8(27). Doi no: 10.17485/ijst/2015/v8i27/81054.
3. Jiang P, Xia H, He Z, Wang Z. Design of a water environental
monitoring system based on wireless sensor network.
Sensors. 2009; 9(8):6411–34. Doi: 10.3390/s90806411.
4. He D, Zhang LX. The Water Quality Monitoring System
Based on WSN. 2nd International Conference on Consumer
Electronics, Communications and Networks (CECNet).
2012 Apr 21-23. p. 3661–64. Doi: 978-1-4577-1415-3
5. Wiranto G, Maulana YY, Hermida IDP, Syamsu I, Mahmudin
D. Integrated Online Water Quality Monitoring: An
Application for Shrimp Aquaculture Data Collection and
Automation. International Conference on Smart Sensors
and Application (ICSSA). 2015. p. 1–4. Doi: 978-1-4799-
7364-4.
6. Jiang P. Survey on Key Technology of WSN-Based Wetland
Water Quality Remote Real-Time Monitoring System. Chin
J Sens Actuat. 2007; 20:183–6.
7. Jiang P, Kong Y. Design of Data Video Base Station of
WSNs Oriented Water Environment Monitoring. Chin J
Sens Actuat. 2008 Jul 29-31; 21:1581–85.
8. EmNetLLC Technology. Available from: http://www.heliosware.
com/technology.html. 16/01/2009.
9. The CSIRO ICT Centre. Wireless Sensor Network Devices.
Available from:http://www.ict.csiro.au/ page.pHp?cid=87.
16/01/2009.
10. Seders LA, Shea CA, Lemmon MD, Maurice PA, Talley JW,
LakeNet: An Integrated Sensor Network for Environmental
Sensing in Lakes. Environm Eng Sci. 2007; 24:183–91.
11. O’Flynn B, Catala MF, Harte S, O’Mathuna C, Cleary J,
Slater C, Regan F, Diamond D, MurpHy H. Smart Coast:
A Wireless Sensor Network for Water Quality Monitoring.
32nd IEEE Conference on Local Computer Networks, LCN
2007, Dublin, Ireland. 2007 Oct 15-18. p. 815–16.
12. Yang X, Ong KG, Dreschel WR, Zeng K, Mungle CS, Grimes
CA. Design of a Wireless Sensor Network for Long-Term,
in-situ Monitoring of an Aqueous Environment. Sensors.
2002; 2:455–72.
13. Islam MR, Kim J. Step-by-Step Approach for Energy-efficient
Wireless sensor Network. IETE Technical Review.
2012 Jul-Aug; 29(4):336–45.
14. Rasin Z, Abdullah MR. Water quality monitoring system
using zigbee based wireless sensor network. International
Journal of Engineering and Technology. 2012 May;
9(10):24–8.
15. Hsuech CT, Li YW, Wen CY, Quyang YD. Secure adoptive
Topology control for wireless ad-hoc sensor networks. Sensors.
2010; 1251–78.
16. Kavitha T, Sridharan D. Security Vulnerabilities in Wireless
Sensor Networks: A Survey. Journal of Information Assurance
and Security. 2010; 5:031–044.
17. Hill J et al. System Architecture Directions for Networked
Sensors. 9th int’l conf Architectural Support for Programming
Languages and Operating Systems ACM Press. 2000.
p. 93–104.
18. Ashok J, Thirumoorthy P. Design Considerations for implementing
an Optimal Battery Management System of a
Wireless Sensor Node. Indian Journal of Science and Technology.
2011; 1255–9.
19. Chaamwe N. Wireless Sensor Networks for Water Quality
Monitoring: A case study of Zambia. IEEE 4th International
Conference on Bio-informatics and Bio-Medical Engineering
(iCBBE); 2010 Jun.
20. Global Water User Manual; 2007.
21. Memsic. Xserve User Manual; 2007.
22. Levis P, Gay D. TinyOS Programming. Cambridge University
Press; 2009.
23. Ning LP et al. Tiny ECC: A Configurable Library for Elliptical
Curve Cryptography in Wireless Sensor Networks.
7th International Conference on Information Processing in
Sensor Networks SPOTS Track; 2008 Apr.
24. He D, Zhang LX. The Water quality monitoring system
based on WSN. IEEE 2nd International Conference on
Consumer Electronics, Communications and Networks
(CECNet). 2012.
25. Moon AH, Khan UI et al. Practical implementation of WSN
based data acquisition system with external connectivity.
IEEE Conference on ICMIRA. 2013. p. 77–81.
26. Walters JP, Liang Z, Shi W, Chaudhary V. Wireless sensor
network security: A Survey. Security in Distributed Grid
and Pervasive Computing. CRC Press; 2001.
27. Moon AH, Shah NA, Ummer I, Adil A. Simulating and
Analyzing Security Attacks in WSN Using Qualnet. IEEE
Conference on ICMIRA. 2013. p. 68–76.
28. Kishore R, Budwa HS. High Performance Scalar Multiplication
for ECC. International Conference on Computer
Communication and Informatics. 2013.
Admin
Site Admin
 
Posts: 203
Joined: Wed Sep 20, 2017 9:55 am

by Admin » Thu Apr 19, 2018 10:11 am

16. Devi B. M., Abirami N. A. Real time system for determination of drinking water quality // International Journal of Computer Science and Mobile Computing. – 2014. Vol. 3. Issue. 9. P.732 – 740.

Abstract: Clean drinking water is important for health and well being of all humans. Assessment of quality of water in large water distribution systems involves taking of random water samples and testing it in laboratories. Since this process is time consuming and requires man power, this paper presents an approach to determine the quality of water automatically using low cost and in-pipe sensors. Here an array of sensor node is developed to assess the quality of water. Algorithms are developed for fusing the data collected by the sensors. ZigBee transceiver and GSM transmitters are used to transmit the collected data to the server. This paper also provides the techniques to resolve water contamination.

Main Figures:
ImageImage

References
[1] Theofanis P. Lambrou, Christos C. Anastasiou, Christos G. Panayiotou, and Marios M. Polycarpou “A Low-Cost Sensor Network for Real Time Monitoring and Contamination Detection in Drinking Water Distribution Systems” IEEE SENSORS JOURNAL, VOL.77, NO. 8, pp 2765-2772, April 2014.
[2] T.P. Lambrou, C.G. Panayiotou and C.C. Anastasiou, “A Low-Cost System for Real Time Monitoring and Assessment of Potable Water Quality at Consumer Sites”, in IEEE Sensors journal, pp 28-31 Oct 2012.
[3] S. Zhuiykov, “Solid-state sensors monitoring parameters of water quality for the next generation of wireless sensor networks”, Sensors and Actuators B: Chemical, Volume 161, Issue 1, pp 1-20, 2012.
[4] M. Sophocleous, M. Glanc, Monika, J. Atkinson and E. Garcia-Breijo, “The effect on performance of fabrication parameter variations of thick- film screen printed silver/silver chloride potentiometric reference electrodes”, Sensors and Actuators A Physical, 197, 1-8, 2013.
[5] J. Atkinson, John, M. Glanc,M. Prakorbjanya, M. Sophocleous, R. Sion and E. Garcia-Breijo, “Thick film screen printed environmental and chemical sensor array reference electrodes suitable for subterranean and subaqueous deployments”, Microelectronics International, 30, 92-98, 2013.
[6] R. Martinez Manez, J. Soto, E. Garcia Breijo, J. Ibanez Civera, E. Gadea Morant, “System for determining water quality with thick-film multisensor,” IEEE Electron Devices 2005.
[7] R. Martinez-Manez, J. Soto, E. Garca-Breijo, L. Gil, J. Ibanez, E. Gadea, “A multisensor in thick-film technology for water quality control”, Sensors and Actuators A: Physical, Volume 120, Issue 2, 2005.
[8] P. Corke, T. Wark, R. Jurdak, H. Wen, P. Valencia, D. Moore, “Environmental Wireless Sensor Networks”, Proceedings of the IEEE , vol.98, no.11, pp.1903-1917, Nov. 2010.
[9] A. Jonathan, M. Housh, L. Perelman and A. Ostfeld “A dynamic thresholds scheme for contaminant event detection in water distribution systems”, in Water research, vol. 47, no. 5,pp. 1899-1908, 2013.
[10] C. Jimenez-Jorquera, J. Orozco and A. Baldi, ISFET Based “Microsensors for Environmental Monitoring”, in Sensors, vol.10, pp. 61-83, 2010.
[11] J.V Capella, A. Bonastre, R. Ors and M. Peris, “A Wireless Sensor Network approach for distributed in-line chemical analysis of water”, in Talanta, vol. 80, no. 5, pp. 1789-1798, 2010.
[12] J.V Capella, A. Bonastre, R. Ors and M. Peris, “In line river monitoring of nitrate concentration by means of a Wireless Sensor Network with energy harvesting”, in Sensors and Actuators B: Chemical, vol.177, pp. 419-427, 2013.
[14] S. Sudevalayam and P. Kulkarni, “Energy harvesting sensor nodes: Survey and implications”, in IEEE Communications Surveys & Tutorials, vol.13, no. 3, pp. 443-461, 2013.
[15] G. Tuna and K. Gulez, “Energy harvesting techniques for industrial wireless sensor networks”, in Industrial Wireless Sensor Networks: Applications, Protocols, Standards, and Products, CRC Press, 2013.
[16] A. Whittle, M. Allen, A. Preis, M. Iqbal, “Sensor networks for monitoring and control of water distribution systems”, in the 6th Conference on Structural Health Monitoring of Intelligent Infrastructure, 2013.
[17] KAPTA 3000-AC4 Probe, “KAPTA 3000-AC4 Product Technical Datasheet”, 2014.
Admin
Site Admin
 
Posts: 203
Joined: Wed Sep 20, 2017 9:55 am

by Admin » Thu Apr 19, 2018 10:55 am

17. Geetha S., Gouthami S. Internet of things enabled real time water quality monitoring system // Smart Water. – 2017. Vol.2. P. 1-19.

Abstract: Smart solutions for water quality monitoring are gaining importance with advancement in communication technology. This paper presents a detailed overview of recent works carried out in the field of smart water quality monitoring. Also, a power efficient, simpler solution for in-pipe water quality monitoring based on Internet of Things technology is presented. The model developed is used for testing water samples and the data uploaded over the Internet are analyzed. The system also provides an alert to a remote user, when there is a deviation of water quality parameters from the pre-defined set of standard values.

Main Figures:
Image

Image

Image

Image

References
Alessio B, Walter D, Valerio P, Antonio P (2016) Integration of Cloud computing and Internet of Things: A survey. Futur Gener Comput Syst 56:684–700

Al-Fuqaha A et al (2015) Internet of Things: A Survey on Enabling Technologies, Protocols, and Applications. IEEE Commun Surv Tutorials 17(4):2347–2376

Andrea Z, Nicola B, Angelo C, Lorenzo V, Michele Z (2014) Internet of Things for Smart Cities. IEEE Internet Things J 1(1):22–32

Anthony F, Aloys N, Hector J, Maria C, Albino J, Samuel B (2014) Wireless Sensor Networks for Water Quality Monitoringand Control within Lake Victoria Basin: Prototype Development. Wirel Sens Netw 6:281–290
Azedine C, Antoine G, Patrick B, Michel M (2000) Water quality monitoring using a smart sensing system. Measurement:219–224

Bhatt Jayti, Jignesh Patoliya (2016), “IoT based water quality monitoring system”, In: Proc of 49th IRF Int Conf, 21 Feb 2016

Biljana L, Risteska S, Kire VT (2017) A review of Internet of Things for smart home: Challenges and solutions. J Clean Prod 140(3):1454–1464

Bushra R, Mubashir HR (2016) Applications of wireless sensor networks for urban areas: A survey. J Netw Comput Appl 60:192–219

Central Ground Water Board (2017) Ministry of Water Resources, River Development and Ganga Rejuvenation,
Government of India. http://cgwb.gov.in/. Accessed 24 July 2017

Christie R, Mallory C, Jared L, Alan M (2014) Remote Delay Tolerant Water Quality Monitoring. In: IEEE global humanitarian technology conference, 10–13 Oct 2014

Eliades D, Lambrou T, Panayiotou C, Polycarpou M (2014) Contamination Event Detection in Water Distribution Systems using a Model-Based Approach. In: 16th Conference on Water Distribution System Analysis. 14–17 July 2014

Francesco A, Filippo A, Carlo GC, Anna ML (2015) A Smart Sensor Network for Sea Water Quality Monitoring. IEEE
Sensors J 15(5):2514–2522

Gerson G, Christopher B, Stephen M, Richard O (2012) Real-time Detection of Water Pollution using Biosensors and Live Animal Behavior Models, In: 6th eResearch Australasia Conference, 28 Oct −1 Nov 2012

Goib W, Yudi Y, Dewa P, Iqbal S, Dadin M (2015) Integrated online water quality monitoring. In: International
conference on smart sensors and application, 26–28 May 2015
Admin
Site Admin
 
Posts: 203
Joined: Wed Sep 20, 2017 9:55 am

by Admin » Wed Apr 25, 2018 4:22 pm

18. Bhagde P, Dabhagde M, Yende R, Mharaskolle S, Kuttarmare S, Umare A, Chimurkar M. P. Water Quality Monitoring And Distribution IOT Based Economical Project //IJSRSET. – 2018. Vol.4. Issue 6. P. 114-118.

Abstract:
Now a day water is a vital resource for life, and economy. One of the most serious issue to solve and manage the water scarcity and distribution of water contains employee work and consumed time for distribute the water to each area. Purity of water for human health is most serious issue. Water monitoring and impurity removal is important task. Exiting systems uses clorinization for purification of water but only clorinization for purification is not helpful. Other impurity remain in water. To check that impurity by using turbidity sensor check purity of water. PH sensor use and flow sensor use for equal distribution of water. This system is Real time monitoring system. This paper is reconfigurable smart sensor interface device for water quality monitoring using IOT based environment.

Main Figures:
Image Image

References
[1]. Nikhil Kedia, Water Quality Monitoring for Rural Areas- A Sensor Cloud Based Economical Project, in 1st International Conference on Next Generation Computing Technologies (NGCT-2015) Dehradun, India, 4-5 September 2015. 978-1-4673-6809-4/15/$31.00 ©2015 IEEE
[2]. Sokratis Kartakis, Weiren Yu, Reza Akhavan, and Julie A. McCann, 2016 IEEE First International Conference on Internet-of-Things Design and Implementation, 978-1-4673-9948-7/16 © 2016IEEE
[3]. M N Barabde, S R Danve, "A Review on Water Quality Monitoring System", International Journal of VLSI and Embedded Systems-IJVES, Vol 06, Article 03543; March 2015, pp. 1475-1479.
[4]. Turkane Satish, Kulkarni Amruta, "Solar Powered Water Quality Monitoring system using wireless Sensor Network", IEEE Conference on
[5]. Automation, Computing, Communication, Control and Compressed sensing, IEEE, 2013, pp. 281-285.
[6]. K. Elissa, "Title of paper if known," unpublished.
[7]. R. Nicole, "Title of paper with only first word capitalized," J. Name Stand. Abbrev., in press.
[8]. Y. Yorozu, M. Hirano, K. Oka, and Y. Tagawa, "Electron spectroscopy studies on magneto-optical media and plastic substrate interface," IEEE Transl. J. Magn. Japan, vol. 2, pp. 740-741, August1987 Digests 9th Annual Conf. Magnetics Japan, p. 301, 1982].
[9]. M. Young, The Technical Writer’s Handbook. Mill Valley, CA: University Science, 1989.
Admin
Site Admin
 
Posts: 203
Joined: Wed Sep 20, 2017 9:55 am

by Admin » Sat Apr 28, 2018 11:57 am

19. Lizhong X., Hui G., Chenming L., Aiye S. System Design of Water Quality Monitoring Robot with Automatic Navigation and Self-test Capability // International Journal of Control and Automation. – 2013. Vol.6, No.5. P.67-82.

Abstract: This paper proposes a water quality monitoring system of underwater robot with self-test and diagnosis capability. The system consists of underwater robot, water quality data collection module, self-test and diagnosis module, wireless communication module, and shore-based facility. The measurement results from each sensor of water quality data collection module are transmitted to the built-in micro-processor of the underwater robot. And the self-test and diagnosis module based on DSP connects with the built-in microprocessor through RS232. The self-test and diagnosis module conducts wavelet transform for the sensor information, generating extreme points of the wavelet transform, which are used to detect the abnormal state of the current system. The threshold method is introduced to reduce the influence of the noise. The disturbance of the noise can be alleviated by setting threshold for high frequency parameters of the wavelet transform. The exceptional information was detected by the self-test module and the water quality data information was transmitted to the shore-based facility through the wireless communication module. The shore-based facility can process, analyze and determine the collected information, and then give feedback to the underwater robot. The feasibility of the system design and the rationality of the water quality parameter measurement results were verified by experiments and on-site tests.


Main Figures:
Image

References
[1] Q. L. Wu, Y. Liang, Y. X. Sun, C. M. Zhang and P. Z. Liu, “Application of GPRS Technology in Water Quality Monitoring System”, Proceedings of World Automation Congress(WAC), (2010), September 19-23; Kobe, Japan.
[2] A. Giremus, J. -Y. Tourneret and A. Doucet, “A Fixed-Lag Particle Filter for the Joint Detection / Compensation of Interference Effects in GPS Navigation”, J. IEEE Transactions on Signal Processing, vol. 58, (2010), pp. 6066-6079.
[3] K. D. Rao, M. N. S. Swamy and E. I. Plotkin, “GPS Navigation with Increased Immunity to Modeling Errors”, J. IEEE Transactions on Aerospace and Electronic Systems, vol. 40, (2004), pp. 2-11.
[4] S. Peng and X. H. Zhao, “A Review of Uncertainty Methods Employed in Water Quality Modeling”, Proceedings of International Conference of Environmental Science and Information Application Technology, (2009) July 4-5; Wuhan, China.
[5] B. A. Cox, “A review of currently available in-stream waterquality models and their applicability for simulating dissolved oxygen in lowland rivers”, J. The Science of the Total Environment, vol. 314, (2003), pp. 335-377.
[6] S. M. Duan, “An improved federated filtering method for integrated navigation system of Autonomous Underwater Vehicle”, Proceedings of the 7th International Conference of System Simulation and Scientific Computing, (2008), October 10-12; Beijing, China.
[7] J. M. Chen, X. B. Wu and G. H. Chen, “REBAR: A Reliable and Energy Balanced Routing Algorithm for UWSNs”, Proceedings of International Conference of n Grid and Cooperative Computing, (2008), October 24-26; Shenzhen, China.
[8] N. Cohen and S. Weiss, “Complex Floating Point—A Novel Data Word Representation for DSP Processors”, J. IEEE Transactions on Circuits and Systems, vol. 59, (2012), pp. 2252-2262.
[9] C. Heegard, J. T. Coffey, S. Gummadi, P. A. Murphy, R. Provencio,E. J. Rossin, S. Schrum and M. B. Shoemake, “High-Performance Wireless Ethernet”, J. IEEE Communications Magazine, vol. 39, (2001), pp. 64-73.
[10] G. P. Tan, X. Y. Ni, X. Q. Liu, C. Y. Qu and L. Y. Tang, “Real-time multicast with network coding in mobile ad-hoc networks”, J. Intelligent Automation and Soft Computing, vol. 18, (2012), pp. 783-794.
[11] Y. H. Li, J. Zhao, M. Y. Ju and X. H. Yin, “New method to improve the channel capacity and capacity stability of 4-element MIMO systems with close antenna spacing”, J. Communications, vol. 32, (2011), pp. 86-92.
[12] J. G. Wang, G. X. Wu and L. Wan, “Sensor Fault Diagnosis for Underwater Robots”, Proceedings of the 7th World Congress on Control and Automation, vol. 12, (2008), pp. 254-259; Chongqing, China.
[13] C. T. Shi, R. B. Zhao and B. L. Liu, “Layered Self-healing Software Architecture of AUV Based on Micro-reboot”, Proceedings of International Workshop on Intelligent Systems and Applications, (2009), pp. 1-4; WuHan, China.
[14] H. O. Madsen, P. Christensen and K. Lauridsen, “Securing the operational reliability of an autonomous mini-submarine”, J. Reliability Engineering and System Safety, vol. 68, (2000), pp. 7-16.
[15] D. M. Xu and L. Gao, “Wavelet transform and its application to autonomous underwater vehicle control system fault detection”, Proceedings of Underwater Technology, (2000), pp. 99-104; Tokyo, Japan.
[16] X. G. Zhu, B. R. Hong and D. M. Wang, “Implementation of time-scale transformation based on continuous wavelet theory”, J. Systems Engineering and Electronics, vol. 11, (2000), pp. 32-37.
[17] Q. H. Max Meng, L. M. Dan and X. N. Li, “A Real-Time Generic Animated Simulator for Robot Manipulators”, Proceedings of Electrical and Computer Engineering, vol. 2, (1993), pp. 1077-1080; Vancuver, BC.
[18] M. Juraeva and D. J. Song, “Internet-Based Graphic User Interface for Postprocessor of Computational Fluid Dynamics”, Proceedings of the International Conference on Computational Intelligence for Modelling, Control and Automation, vol. 2, (2005), pp. 636-640.
[19] L. T. Ruiz, S. de Raucourt, Y. Petillot and D. M. Lane, “Concurrent Mapping and Localization Using Sidescan Sonar”, J. IEEE Journal of Oceanic Engineering, vol. 29, (2004).
[20] M. Perrier, L. Brignone and M. Drogou, “Communication Constraints and Requirements for Operating Multiple Unmanned Marine Robots”, Proceedings of the 7th International Offshore and Polar Engineering Conference, (2007), pp. 1053-1058.
[21] S. Zhao, B. He and S. Tian, “A Sonar Data Processing System ofUnderwater Robot Based on C6000 DSP”, Proceedings of the 2nd International Asia Conference on Informatics in Control, Automation and Robotics, vol. 1, (2010), pp. 315-317; Wu Han, China.
[22] C. S. Lam, X. X. Cui, M. C. Wong and Y. D. Han, “Minimum DC-link voltage design of three-phase four-wire active power filters”, J. IEEE 13th Workshop on Control and Modeling for Power Electronics (COMPEL), vol. 1, no. 5, (2012).
[23] E. Kramer, H. Liu, N. Seitz and G Hirzinger, “A Multisensory Linear Actuator System”, J. IEEE Transactions on Mechatronics, vol. 7, (2002), pp. 182-185.
[24] J. W. Zhu, “The Development and Design of the Gas-Liquid Two-Phase Flow-meter System Based on DSP”, Proceedings of International Conference on Advanced Computer Theory and Engineering, (2008), pp. 978-981, Phuket, Tailand.
[25] Z. Ghrairi, K. A. Hribernik, C. Hans and K. -D. Thoben, “Intelligent wireless communication devices for efficient data transfer and machine control”, Proceedings of International Conference on Communications, Computing and Control Applications (CCCA), (2012), pp. 1-6; Marseilles, France.
[26] T. Suzuki, M. Bandai and T. Watanabe, Eds., “DispersiveCast: Dispersive Packets Transmission to Multiple Sinks for Energy Saving in Sensor Networks”, Proceedings of the 17th Annual IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, (2006) September 11-14; Helsinki, Finland.
[27] A. Y. Shi and M. Tang, “Super-resolution of remotely sensed images based on map and Discontinuity Adaptive markov random field”, J. Intelligent Automation and SoftComputing, vol. 17, no. 7, (2011).
[28] G. Cena, A. Valenzano and S. Vitturi, “Hybrid wired/wireless networks for real-time industrial communications”, J. IEEE Ind. Electron. Mag., vol. 2, (2008), pp. 8 -20.
[29] A. Willig, “Recent and emerging topics in wireless industrial communications: A selection”, J. IEEE Trans. Ind. Informat., vol. 4, (2008), pp. 102 -124.
[30] A. Alessandri, T. Hawkinson, A. J. Healey and G. Veruggio, “Robust model-based fault diagnosis for unmanned underwater robots using sliding mode-observers”, Proceedings of Int. Symposium Unmanned Untethered Submersible Technology, vol. 12, (1999), pp. 1-8.
Admin
Site Admin
 
Posts: 203
Joined: Wed Sep 20, 2017 9:55 am

by Admin » Thu May 17, 2018 1:41 pm

20. Gutierrez J., Villa-Medina J.F., Nieto-Garibay A., and Porta-Gandara M.A. Automated Irrigation System Using a Wireless Sensor Network and GPRS Module // IEEE Trans. Instrum. Meas., vol. 30. P. 1-11.

Abstract: An automated irrigation system was developed to optimize water use for agricultural crops. The system has a distributed wireless network of soil-moisture and temperature sensors placed in the root zone of the plants. In addition, a gateway unit handles sensor information, triggers actuators, and transmits data to a web application. An algorithm was developed with threshold values of temperature and soil moisture that was programmed into a microcontroller-based gateway to control water quantity. The system was powered by photovoltaic panels and had a duplex communication link based on a cellular-Internet interface that allowed for data inspection and irrigation scheduling to be programmed through a web page. The automated system was tested in a sage crop field for 136 days and water savings of up to 90% compared with traditional irrigation practices of the agricultural zone were achieved. Three replicas of the automated system have been used successfully in other places for 18 months. Because of its energy autonomy and low cost, the system has the potential to be useful in water limited geographically isolated areas.

Main Figures:

Image Image
Image Image
Image Image

References
[1] W. A. Jury and H. J. Vaux, “The emerging global water crisis: Managing
scarcity and conflict between water users,” Adv. Agronomy, vol. 95,
pp. 1–76, Sep. 2007.
[2] X. Wang, W. Yang, A. Wheaton, N. Cooley, and B. Moran, “Efficient
registration of optical and IR images for automatic plant water stress
assessment,” Comput. Electron. Agricult., vol. 74, no. 2, pp. 230–237,
Nov. 2010.
[3] G. Yuan, Y. Luo, X. Sun, and D. Tang, “Evaluation of a crop water
stress index for detecting water stress in winter wheat in the North China
Plain,” Agricult. Water Manag., vol. 64, no. 1, pp. 29–40, Jan. 2004.
[4] S. B. Idso, R. D. Jackson, P. J. Pinter, Jr., R. J. Reginato, and
J. L. Hatfield, “Normalizing the stress-degree-day parameter for environmental
variability,” Agricult. Meteorol., vol. 24, pp. 45–55, Jan. 1981.
[5] Y. Erdem, L. Arin, T. Erdem, S. Polat, M. Deveci, H. Okursoy, and
H. T. Gültas, “Crop water stress index for assessing irrigation scheduling
of drip irrigated broccoli (Brassica oleracea L. var. italica),” Agricult.
Water Manag., vol. 98, no. 1, pp. 148–156, Dec. 2010.
[6] K. S. Nemali and M. W. Van Iersel, “An automated system for controlling
drought stress and irrigation in potted plants,” Sci. Horticult.,
vol. 110, no. 3, pp. 292–297, Nov. 2006.
[7] S. A. O’Shaughnessy and S. R. Evett, “Canopy temperature based system
effectively schedules and controls center pivot irrigation of cotton,”
Agricult. Water Manag., vol. 97, no. 9, pp. 1310–1316, Apr. 2010.
[8] R. G. Allen, L. S. Pereira, D. Raes, and M. Smith, Crop
Evapotranspiration-Guidelines for Computing Crop Water
Requirements—FAO Irrigation and Drainage Paper 56. Rome, Italy:
FAO, 1998.
[9] S. L. Davis and M. D. Dukes, “Irrigation scheduling performance by
evapotranspiration-based controllers,” Agricult. Water Manag., vol. 98,
no. 1, pp. 19–28, Dec. 2010.
[10] K. W. Migliaccio, B. Schaffer, J. H. Crane, and F. S. Davies, “Plant
response to evapotranspiration and soil water sensor irrigation scheduling
methods for papaya production in south Florida,” Agricult. Water
Manag., vol. 97, no. 10, pp. 1452–1460, Oct. 2010.
[11] J. M. Blonquist, Jr., S. B. Jones, and D. A. Robinson, “Precise irrigation
scheduling for turfgrass using a subsurface electromagnetic soil moisture
sensor,” Agricult. Water Manag., vol. 84, nos. 1–2, pp. 153–165,
Jul. 2006.
[12] O. M. Grant, M. J. Davies, H. Longbottom, and C. J. Atkinson,
“Irrigation scheduling and irrigation systems: Optimising irrigation efficiency
for container ornamental shrubs,” Irrigation Sci., vol. 27, no. 2,
pp. 139–153, Jan. 2009.
[13] Y. Kim, R. G. Evans, and W. M. Iversen, “Remote sensing and control of
an irrigation system using a distributed wireless sensor network,” IEEE
Trans. Instrum. Meas., vol. 57, no. 7, pp. 1379–1387, Jul. 2008.
[14] Y. Kim and R. G. Evans, “Software design for wireless sensor-based
site-specific irrigation,” Comput. Electron. Agricult., vol. 66, no. 2,
pp. 159–165, May 2009.
[15] D. K. Fisher and H. A. Kebede, “A low-cost microcontroller-based
system to monitor crop temperature and water status,” Comput. Electron.
Agricult., vol. 74, no. 1, pp. 168–173, Oct. 2010.
[16] Y. Kim, J. D. Jabro, and R. G. Evans, “Wireless lysimeters for realtime
online soil water monitoring,” Irrigation Sci., vol. 29, no. 5,
pp. 423–430, Sep. 2011.
[17] O. Mirabella and M. Brischetto, “A hybrid wired/wireless networking
infrastructure for greenhouse management,” IEEE Trans. Instrum. Meas.,
vol. 60, no. 2, pp. 398–407, Feb. 2011.
[18] I. F. Akyildiz, W. Su, Y. Sankarasubramaniam, and E. Cayirci, “A survey
on sensor networks,” IEEE Commun. Mag., vol. 40, no. 8, pp. 104–112,
Aug. 2002.
[19] J. Yick, B. Mukherjee, and D. Ghosal, “Wireless sensor network survey,”
Comput. Netw., vol. 52, no. 12, pp. 2292–2330, Aug. 2008.
[20] M. Winkler, K.-D. Tuchs, K. Hughes, and G. Barclay, “Theoretical and
practical aspects of military wireless sensor networks,” J. Telecommun.
Inf. Technol., vol. 2, pp. 37–45, Apr./Jun. 2008.
[21] M. P. Durisic, Z. Tafa, G. Dimic, and V. Milutinovic, “A survey of
military applications of wireless sensor networks,” in Proc. MECO,
Jun. 2012, pp. 196–199.
[22] M. C. Rodríguez-Sánchez, S. Borromeo, and J. A. Hernández-Tamames,
“Wireless sensor networks for conservation and monitoring cultural
assets,” IEEE Sensors J., vol. 11, no. 6, pp. 1382–1389, Jun. 2011.
[23] G. López, V. Custodio, and J. I. Moreno, “LOBIN: E-textile and
wireless-sensor-network-based platform for healthcare monitoring in
future hospital environments,” IEEE Trans. Inf. Technol. Biomed.,
vol. 14, no. 6, pp. 1446–1458, Nov. 2010.
[24] J. M. Corchado, J. Bajo, D. I. Tapia, and A. Abraham, “Using
heterogeneous wireless sensor networks in a telemonitoring system
for healthcare,” IEEE Trans. Inf. Technol. Biomed., vol. 14, no. 2,
pp. 234–240, Mar. 2010.
[25] G. X. Lee, K. S. Low, and T. Taher, “Unrestrained measurement of
arm motion based on a wearable wireless sensor network,” IEEE Trans.
Instrum. Meas., vol. 59, no. 5, pp. 1309–1317, May 2010.
[26] D.-M. Han and J.-H. Lim, “Smart home energy management system
using IEEE 802.15.4 and ZigBee,” IEEE Trans. Consum. Electron.,
vol. 56, no. 3, pp. 1403–1410, Aug. 2010.
[27] C. Gomez and J. Paradells, “Wireless home automation networks: A
survey of architectures and technologies,” IEEE Commun. Mag., vol. 48,
no. 6, pp. 92–101, Jun. 2010.
[28] M. Bertocco, G. Gamba, A. Sona, and S. Vitturi, “Experimental characterization
of wireless sensor networks for industrial applications,” IEEE
Trans. Instrum. Meas., vol. 57, no. 8, pp. 1537–1546, Aug. 2008.
[29] V. C. Gungor and G. P. Hancke, “Industrial wireless sensor networks:
Challenges, design principles, and technical approaches,” IEEE Trans.
Ind. Electron., vol. 56, no. 10, pp. 4258–4265, Oct. 2009.
[30] L. Hou and N. W. Bergmann, “Novel industrial wireless sensor networks
for machine condition monitoring and fault diagnosis,” IEEE Trans.
Instrum. Meas., vol. 61, no. 10, pp. 2787–2798, Oct. 2012.
[31] A. Carullo, S. Corbellini, M. Parvis, and A. Vallan, “A wireless sensor
network for cold-chain monitoring,” IEEE Trans. Instrum. Meas.,
vol. 58, no. 5, pp. 1405–1411, May 2009.
[32] A. Araujo, J. Garcia-Palacios, J. Blesa, F. Tirado, E. Romero,
A. Samartin, and O. Nieto-Taladriz, “Wireless measurement system
for structural health monitoring with high time-synchronization accuracy,”
IEEE Trans. Instrum. Meas., vol. 61, no. 3, pp. 801–810,
Mar. 2012.
[33] P. Corke, T. Wark, R. Jurdak, H. Wen, P. Valencia, and D. Moore,
“Environmental wireless sensor networks,” Proc. IEEE, vol. 98, no. 11,
pp. 1903–1917, Nov. 2010.
[34] L. M. Oliveira and J. J. Rodrigues, “Wireless sensor networks: A survey
on environmental monitoring,” J. Commun., vol. 6, no. 2, pp. 143–151,
Apr. 2011.
[35] H.-C. Lee, Y.-M. Fang, B.-J. Lee, and C.-T. King, “The tube: A
rapidly deployable wireless sensor platform for supervising pollution
of emergency work,” IEEE Trans. Instrum. Meas., vol. 61, no. 10,
pp. 2776–2786, Oct. 2012.
[36] H.-C. Lee, A. Banerjee, Y.-M. Fang, B.-J. Lee, and C.-T. King, “Design
of a multifunctional wireless sensor for in-situ monitoring of debris
flows,” IEEE Trans. Instrum. Meas., vol. 59, no. 11, pp. 2958–2967,
Nov. 2010.
[37] N. Wang, N. Zhang, and M. Wang, “Wireless sensors in agriculture and
food industry—Recent development and future perspective,” Comput.
Electron. Agricult., vol. 50, no. 1, pp. 1–14, Jan. 2006.
[38] D. D. Chaudhary, S. P. Nayse, and L. M. Waghmare, “Application of
wireless sensor networks for green house parameters control in precision
agriculture,” Int. J. Wireless Mobile Netw., vol. 3, no. 1, pp. 140–149,
Feb. 2011.
[39] P. Mariño, F. P. Fontan, M. A. Dominguez, and S. Otero, “An experimental
ad-hoc WSN for the instrumentation of biological models,” IEEE
Trans. Instrum. Meas., vol. 59, no. 11, pp. 2936–2948, Nov. 2010.
[40] M. Johnson, M. Healy, P. van de Ven, M. J. Hayes, J. Nelson, T. Newe,
and E. Lewis, “A comparative review of wireless sensor network mote
technologies,” in Proc. IEEE Sensors, Oct. 2009, pp. 1439–1442.
[41] J. S. Lee, Y. W. Su, and C. C. Shen, “A comparative study of wireless
protocols: Bluetooth, UWB, ZigBee, and Wi-Fi,” in Proc. IEEE 33rd
Annu. Conf. IECON, Nov. 2007, pp. 46–51.
[42] M. R. Frankowiak, R. I. Grosvenor, and P. W. Prickett, “A review
of the evolution of microcontroller-based machine and process monitoring,”
Int. J. Mach. Tool Manuf., vol. 45, nos. 4–5, pp. 573–582,
Apr. 2005.
[43] C. Kompis and P. Sureka, “Power management technologies to enable
remote and wireless sensing,” ESP KTN, Teddington, U.K., Tech. Rep.,
May 2010.
[44] M. T. Penella and M. Gasulla, “Runtime extension of low-power wireless
sensor nodes using hybrid-storage units,” IEEE Trans. Instrum. Meas.,
vol. 59, no. 4, pp. 857–865, Apr. 2010.
[45] W. K. G. Seah, Z. A. Eu, and H.-P. Tan, “Wireless sensor networks
powered by ambient energy harvesting (WSN-HEAP)—Survey and
challenges,” in Proc. 1st Int. Conf. Wireless VITAE, May 2009, pp. 1–5.
[46] Y. K. Tan and S. K. Panda, “Self-autonomous wireless sensor nodes
with wind energy harvesting for remote sensing of wind-driven wildfire
spread,” IEEE Trans. Instrum. Meas., vol. 60, no. 4, pp. 1367–1377,
Apr. 2011.
[47] E. Sardini and M. Serpelloni, “Self-powered wireless sensor for air temperature
and velocity measurements with energy harvesting capability,”
IEEE Trans. Instrum. Meas., vol. 60, no. 5, pp. 1838–1844, May 2011.
[48] I. Marin, E. Arceredillo, A. Zuloaga, and J. Arias,
“Wireless sensor networks: A survey on ultra-low poweraware
design,” in Proc. WASET, vol. 8. Oct. 2005,
pp. 1–6.
[49] S. Kolli and M. Zawodniok, “Energy-efficient multi-key security scheme
for wireless sensor network,” in Proc. IEEE 34th Conf. LCN, Oct. 2009,
pp. 937–944.
[50] J. Lin, W. Xiao, F. L. Lewis, and L. Xie, “Energy-efficient distributed
adaptive multisensor scheduling for target tracking in wireless sensor
networks,” IEEE Trans. Instrum. Meas., vol. 58, no. 6, pp. 1886–1896,
Jun. 2009.
[51] P. Györke and B. Pataki, “Energy-aware measurement scheduling in
WSNs used in AAL applications,” IEEE Trans. Instrum. Meas., vol. 62,
no. 5, pp. 1318–1325, May 2013.
[52] R. Yan, H. Sun, and Y. Qian, “Energy-aware sensor node design with its
application in wireless sensor networks,” IEEE Trans. Instrum. Meas.,
vol. 62, no. 5, pp. 1183–1191, May 2013.
[53] Q. Wang, W. Yan, and Y. Shen, “N-person card game approach for
solving SET K-COVER problem in wireless sensor networks,” IEEE
Trans. Instrum. Meas., vol. 61, no. 5, pp. 1522–1535, May 2012.
[54] F. Pianegiani, M. Hu, A. Boni, and D. Petri, “Energy-efficient signal
classification in ad hoc wireless sensor networks,” IEEE Trans. Instrum.
Meas., vol. 57, no. 1, pp. 190–196, Jan. 2008.
[55] C. Alippi, G. Anastasi, D. Francesco, and M. Roveri, “An adaptive
sampling algorithm for effective energy management in wireless sensor
networks with energy-hungry sensors,” IEEE Trans. Instrum. Meas.,
vol. 59, no. 2, pp. 335–344, Feb. 2010.
[56] P. Suriyachai, U. Roedig, and A. Scott, “A survey of MAC protocols
for mission-critical applications in wireless sensor networks,” Commun.
Surveys Tuts., vol. 14, no. 2, pp. 240–264, Apr./Jun. 2012.
[57] Wireless Medium Access Control (MAC) and Physical Layer (PHY)
Specifications: Higher-Speed Physical Layer Extension in the 2.4 GHz
Band, IEEE Standard 802.11b, 1999.
[58] Wireless Medium Access Control (MAC) and Physical Layer
(PHY) Specifications for Wireless Personal Area Networks (WPANs),
IEEE Standard 802.15.1, 2002.
[59] Wireless Medium Access Control (MAC) and Physical Layer (PHY)
Specifications: High Rate Wireless Personal Area Networks (WPANs),
IEEE Standard 802.15.3, 2003.
[60] Wireless Medium Access Control (MAC) and Physical Layer
(PHY) Specifications for Low-Rate Wireless Personal Area Networks
(LR-WPANs), IEEE Standard 802.15.4, 2003.
[61] Request for Comments (RFC) 4944-Transmission of IPv6 Packets over
IEEE 802.15.4 Networks, Internet Eng. Task Force, Orlando, FL, USA,
2007.
[62] J. E. Higuera and J. Polo, “IEEE 1451 standard in 6LoWPAN sensor networks
using a compact physical-layer transducer electronic datasheet,”
IEEE Trans. Instrum. Meas., vol. 60, no. 8, pp. 2751–2758, Aug. 2011.
[63] Industrial Communication Network-Fieldbus Specifications-
WirelessHART Communication Network and Communication Profile,
Edition 1.0, Standard IEC/PAS 62591, 2009.
[64] Wireless Systems for Industrial Automation: Process Control and Related
Applications, Standard ISA-100.11a-2009, 2009.
[65] P. Baronti, P. Pillai, V. W. C. Chook, S. Chessa, A. Gotta, and Y. F. Hu,
“Wireless sensor networks: A survey on the state of the art and the
802.15.4 and ZigBee standards,” Comput. Commun., vol. 30, no. 7, pp.
1655–1695, May 2007.
[66] W. Guo, W. M. Healy, and Z. MengChu, “Impacts of 2.4-GHz ISM
band interference on IEEE 802.15.4 wireless sensor network reliability
in buildings,” IEEE Trans. Instrum. Meas., vol. 61, no. 9, pp. 2533–2544,
Sep. 2012.
[67] N. Baker, “ZigBee and Bluetooth strengths and weaknesses for industrial
applications,” Comput. Control Eng. J., vol. 16, no. 2, pp. 20–25,
Apr./May 2005.


<< Предыдущая страница

Admin
Site Admin
 
Posts: 203
Joined: Wed Sep 20, 2017 9:55 am

PreviousNext

Return to Литература по теме

cron

User Menu

Login