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Guidance And Control Of Ocean Vehicles

https://research-information.bris.ac.uk/ws/files/148592447/Water_Quality_monitoring_in_smart_city_rev2.pdf

Water quality monitoring in a smart city: a pilot project

An unmanned aerial vehicle-assisted water quality measurement system (UAMS) was developed for in situ surface water quality measurement. A custom-built hexacopter was equipped with an open-source electronic sensors platform to measure the temperature, electrical conductivity (EC), dissolved oxygen (DO), and pH of water. Electronic components of the system were coated with a water-resistant film, and the hexacopter was assembled with flotation equipment. The measurements were made at thirteen sampling waypoints within a 1.1 ha agricultural pond. Measurements made by an open-source multiprobe meter (OSMM) attached to the unmanned aerial vehicle (UAV) were compared to the measurements made by a commercial multiprobe meter (CMM). Percent differences between the OSMM and CMM measurements for DO, EC, pH, and temperature were 2.1 %, 3.43 %, 3.76 %, and <1.0 %, respectively. The collected water quality data was used to interpret the spatial distribution of measurements in the pond. The UAMS successfully made semiautonomous in situ water quality measurements from predetermined waypoints. Water quality maps showed homogeneous distribution of measured constituents across the pond. The concept presented in this paper can be applied to the monitoring of water quality in larger surface waterbodies.

https://www.mdpi.com/2073-4441/10/3/264/pdf

In Situ Water Quality Measurements Using an Unmanned Aerial Vehicle (UAV) System

The monitoring of farming processes can optimize the use of resources and improve its sustainability and profitability. In fish farms, the water quality, tank environment, and fish behavior must be monitored. Wireless sensor networks (WSNs) are a promising option to perform this monitoring. Nevertheless, its high cost is slowing the expansion of its use. In this paper, we propose a set of sensors for monitoring the water quality and fish behavior in aquaculture tanks during the feeding process. The WSN is based on physical sensors, composed of simple electronic components. The system proposed can monitor water quality parameters, tank status, the feed falling and fish swimming depth and velocity. In addition, the system includes a smart algorithm to reduce the energy waste when sending the information from the node to the database. The system is composed of three nodes in each tank that send the information though the local area network to a database on the Internet and a smart algorithm that detects abnormal values and sends alarms when they happen. All the sensors are designed, calibrated, and deployed to ensure its suitability. The greatest efforts have been accomplished with the fish presence sensor. The total cost of the sensors and nodes for the proposed system is less than 90 €.

Design and deployment of low-cost sensors for monitoring the water quality and fish behavior in aquaculture tanks during the feeding process

Water quality assessment programs for the management of water resources require the collection of water samples for physical, chemical, and biological analyses. Lack of personnel, accessibility of water bodies, and time constraints, especially after natural disasters and emergencies, are some of the challenges of water sampling. To overcome these challenges, a custom-made thief-style water sampling mechanism was developed and mounted on a multirotor unmanned aerial vehicle (UAV) for autonomous water sampling. The payload capacity and endurance of the UAV were determined using an indoor test station. The UAV was equipped with floatation, and electronic components were coated to prevent water damage in the event of a forced landing or for sample collection. Water samples from a 1.1 ha pond were collected with the developed UAV-assisted water sampling system and traditional manual methods. Dissolved oxygen (DO), electrical conductivity (EC), pH, temperature and chloride measurements were made on samples collected with both UAV-assisted and manual methods and compared. Percent differences between the two sampling methods for DO, EC, pH, and temperature were minimal except for chloride level. Percent differences between the two sampling methods for DO, EC, pH, and temperature measurements were 3.6%, 2.3%, 0.76%, and 0.03%, respectively. Measured chloride levels for the manual and UAV-assisted sampling methods were 3.97 and 5.46 mg/L. UAV-assisted water sampling may prove faster and safer than manual water sampling from large surface waters and from difficult to access water bodies.

Evaluation of a UAV-Assisted Autonomous Water Sampling

First testing of an AUV mission planning and guidance system for water quality monitoring and fish behavior observation in net cage fish farming

The sustained and cost-effective monitoring of the water quality within European coastal areas is of growing importance in view of the upcoming European marine and maritime directives, i.e. the increased industrial use of the marine environment. Such monitoring needs mechanisms/systems to detect the water quality in a large sea area at different depths in real time. This paper presents a system for the automated detection and analysis of water quality parameters using an autonomous underwater vehicle. The analysis of discharge of nitrate into Norwegian fjords near aqua farms is one of the main application fields of this AUV system. As carrier platform the AUV “CWolf” from the Fraunhofer IOSB-AST will be used, which is perfectly suited through its modular payload concept. The mission task and the integration of the payload unit which includes the sensor module, the scientific and measurement computer in the AUV carrier platform will be described. Few practice oriented information about the software and interface concept, the function of the several software modules and the test platform with the several test levels to test every module will be discussed.

Modular AUV system for Sea Water Quality Monitoring and Management

Nowadays an accurate modeling of the system to be controlled is essential for reliable autopilot. This paper presents a non-linear model of the autonomous underwater vehicle “CWolf”. Matrices and the corresponding coefficients generate a parameterized representation for added mass, Coriolis and centripetal forces, damping, gravity and buoyancy, using the equations of motion, for all six degrees of freedom. The determination of actuator behaviour by surge tests allows the conversion of propeller revolutions to the respective forces and moments. Based on geometric approximations, the coefficients of the model can be specified by optimization algorithms in “open loop” sea trials. The realistic model is the basis for the subsequent design of the autopilot. The reference variables used in the four decoupled adaptive PID controllers for surge, heading, pitch and heave are provided a “Line of Sight” - guidance system. A constraint criteria optimization determines the required controller parameters. The verification by “closed loop” sea trials ensures the results.

Ralf Taubert

Papers

First testing of an AUV mission planning and guidance system for water quality monitoring and fish behavior observation in net cage fish farming

Modular AUV system for Sea Water Quality Monitoring and Management

Model identification and controller parameter optimization for an autopilot design for autonomous underwater vehicles