Limits...
Mobile sailing robot for automatic estimation of fish density and monitoring water quality.

Koprowski R, Wróbel Z, Kleszcz A, Wilczyński S, Woźnica A, Łozowski B, Pilarczyk M, Karczewski J, Migula P - Biomed Eng Online (2013)

Bottom Line: The final results are stored in a table and can be exported to any numerical environment for further analysis.The purpose of the robot is a non-invasive measurement of the number of fish in water reservoirs and a measurement of the quality of drinking water consumed by humans, especially in situations where local sources of pollution could have a significant impact on the quality of water collected for water treatment for people and when getting to these places is difficult.The systematically used robot equipped with the appropriate sensors, can be part of early warning system against the pollution of water used by humans (drinking water, natural swimming pools) which can be dangerous for their health.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Computer Biomedical Systems, Institute of Computer Science, University of Silesia, Będzińska 39, 41-200, Sosnowiec, Poland. robert.koprowski@us.edu.pl

ABSTRACT

Introduction: The paper presents the methodology and the algorithm developed to analyze sonar images focused on fish detection in small water bodies and measurement of their parameters: volume, depth and the GPS location. The final results are stored in a table and can be exported to any numerical environment for further analysis.

Material and method: The measurement method for estimating the number of fish using the automatic robot is based on a sequential calculation of the number of occurrences of fish on the set trajectory. The data analysis from the sonar concerned automatic recognition of fish using the methods of image analysis and processing.

Results: Image analysis algorithm, a mobile robot together with its control in the 2.4 GHz band and full cryptographic communication with the data archiving station was developed as part of this study. For the three model fish ponds where verification of fish catches was carried out (548, 171 and 226 individuals), the measurement error for the described method was not exceeded 8%.

Summary: Created robot together with the developed software has features for remote work also in the variety of harsh weather and environmental conditions, is fully automated and can be remotely controlled using Internet. Designed system enables fish spatial location (GPS coordinates and the depth). The purpose of the robot is a non-invasive measurement of the number of fish in water reservoirs and a measurement of the quality of drinking water consumed by humans, especially in situations where local sources of pollution could have a significant impact on the quality of water collected for water treatment for people and when getting to these places is difficult. The systematically used robot equipped with the appropriate sensors, can be part of early warning system against the pollution of water used by humans (drinking water, natural swimming pools) which can be dangerous for their health.

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Related in: MedlinePlus

Sample trajectories for the growing number of crossings representing: (a) 50%; (b) 30%; and (c) 10% of the total area. Fish clusters are visible as randomly distributed white dots (set the number of clusters).
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Figure 3: Sample trajectories for the growing number of crossings representing: (a) 50%; (b) 30%; and (c) 10% of the total area. Fish clusters are visible as randomly distributed white dots (set the number of clusters).

Mentions: Sample trajectories for the robot movements were shown in Figure 3. The above limitations were only due to the time of performing iterations. For example, in total about 3 million measurements (simulations) were necessary for the realized change of the number of clusters by one in the range of 1 to 60, at changed frequency of robot’s crossings by every 1% in the range of 10% to 100% of the total area, and 5000 iterations for each of the measured values.


Mobile sailing robot for automatic estimation of fish density and monitoring water quality.

Koprowski R, Wróbel Z, Kleszcz A, Wilczyński S, Woźnica A, Łozowski B, Pilarczyk M, Karczewski J, Migula P - Biomed Eng Online (2013)

Sample trajectories for the growing number of crossings representing: (a) 50%; (b) 30%; and (c) 10% of the total area. Fish clusters are visible as randomly distributed white dots (set the number of clusters).
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3716934&req=5

Figure 3: Sample trajectories for the growing number of crossings representing: (a) 50%; (b) 30%; and (c) 10% of the total area. Fish clusters are visible as randomly distributed white dots (set the number of clusters).
Mentions: Sample trajectories for the robot movements were shown in Figure 3. The above limitations were only due to the time of performing iterations. For example, in total about 3 million measurements (simulations) were necessary for the realized change of the number of clusters by one in the range of 1 to 60, at changed frequency of robot’s crossings by every 1% in the range of 10% to 100% of the total area, and 5000 iterations for each of the measured values.

Bottom Line: The final results are stored in a table and can be exported to any numerical environment for further analysis.The purpose of the robot is a non-invasive measurement of the number of fish in water reservoirs and a measurement of the quality of drinking water consumed by humans, especially in situations where local sources of pollution could have a significant impact on the quality of water collected for water treatment for people and when getting to these places is difficult.The systematically used robot equipped with the appropriate sensors, can be part of early warning system against the pollution of water used by humans (drinking water, natural swimming pools) which can be dangerous for their health.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Computer Biomedical Systems, Institute of Computer Science, University of Silesia, Będzińska 39, 41-200, Sosnowiec, Poland. robert.koprowski@us.edu.pl

ABSTRACT

Introduction: The paper presents the methodology and the algorithm developed to analyze sonar images focused on fish detection in small water bodies and measurement of their parameters: volume, depth and the GPS location. The final results are stored in a table and can be exported to any numerical environment for further analysis.

Material and method: The measurement method for estimating the number of fish using the automatic robot is based on a sequential calculation of the number of occurrences of fish on the set trajectory. The data analysis from the sonar concerned automatic recognition of fish using the methods of image analysis and processing.

Results: Image analysis algorithm, a mobile robot together with its control in the 2.4 GHz band and full cryptographic communication with the data archiving station was developed as part of this study. For the three model fish ponds where verification of fish catches was carried out (548, 171 and 226 individuals), the measurement error for the described method was not exceeded 8%.

Summary: Created robot together with the developed software has features for remote work also in the variety of harsh weather and environmental conditions, is fully automated and can be remotely controlled using Internet. Designed system enables fish spatial location (GPS coordinates and the depth). The purpose of the robot is a non-invasive measurement of the number of fish in water reservoirs and a measurement of the quality of drinking water consumed by humans, especially in situations where local sources of pollution could have a significant impact on the quality of water collected for water treatment for people and when getting to these places is difficult. The systematically used robot equipped with the appropriate sensors, can be part of early warning system against the pollution of water used by humans (drinking water, natural swimming pools) which can be dangerous for their health.

Show MeSH
Related in: MedlinePlus