Artificial lateral line

We develop sensors inspired by lateral line sensing of fish, methods of data acquisition and analysis and apply them to measure, characterize and classify underwater environments.

The latera line is a flow sensing organ of a fish which is sensitive to flow and small fluctuations in water that create turbulence. We have taken the same principle and applied it to make sense of underwater environment in a way that other sensing modalities (vision, sound, etc) cannot do. Lateral lines (both natural and artificial) are distributed and redundant sensor systems and information from them is processed accordingly. Complex natural flows are rich of information and we work on creating methods to perceive and make sense of it.

Classifying natural flows. Artificial lateral lines can perceive flows from a situated perspective (immersed into and interacting with the environment that it is measuring). It can give us a glimpse of what might a fish perceive when swimming in water. We have used artificial lateral lines from fish perspective to understand if fish could distinguish and recognize locations in flow. Results of this analysis have been used to improve the construction of man-made structures in rivers so that they can help fish on their migratory pathways. We have also used artificial lateral lines to classify habitats and to classify river morphology.

Work in robot sensing has been funded by:

• ROBOCADEMY (European Academy for Underwater Robotics) financed by European Commission through Framework 7 in 2014- 2018

• BONUS FISHFIEW (Assessing Fish Passeges by the use of Robotic Fish Sensor) funded by EEIG BONUS and Environmental Investment Center in 2014-2017.

Hydromast sensor for large scale distributed flow sensing

Hydromast is a novel flow sensor inspired by fish lateral line mechanoreceptive organ –neuromast. If the biological neuromast is a microscopic receptor, the hydromast sensor is an upscaled version of this principle. 

The working principle of hydromast is based on simultaneous pressure and acceleration measurements. The erect stem of the hydromast bends and vibrates in flow. The accelerations of the stem movement are modeled using the theory of flow induced vibrations and analysed to translate the vibrations into flow speed and direction values. The differential sensor information is modeled using the Pitot equation and also translated to flow speed values. Fusing those two sources of information together (from pressure fluctuations and accelerations) makes a redundant fault tolerant measuring device. Moreover, hydromasts can be used to create underwater sensor networks for distributed flow measurements. The advantages of this technology is low-cost, scalability, resilience, and the possibility of measuring near surfaces where acoustic methods do not work.

Hydromast datasheet

• Hydromast distributed sensing has been used to classify flows in rivers (Keila river video)

• Measuring wave action in at the bottom of the seabed (Pikakari video)

• Measuring dynamics of thermocline on a continental slope (Keri video)

Hydromast sensor network is installed in Sillamäe harbour for safe navigation of the breathing ships, to Paldiski harbour for save navigation on the fairway and in contemporarily in several other harbours to investigate the impact of waves and currents to harbour structures. 

Hydromast has been funded by:

• LAkHsMI (Sensors for Large Scale Hydrodynamic Imaging of the Ocean) financed by European Union Horizon 2020 grant in 2015- 2019

• Hydromast network installation in Sillamäe harbour has been supported by Prototron funding for creating functional prototypes.

We are building sensors that bring information back from difficult places under extreme conditions.

Those sensors are designed to be fault-tolerant and resilient, to be exploited in harsh environments repeatedly or for long periods of time.  The data in analysed using methods of multi-parameter statistical modelling and machine learning.

Barotrauma sensors for hydropower turbines have been developed to understand if fish can pass and survive during downstream migration. These sensors  are capable of detecting very rapid changes of acceleration (5000g), pressure (100bar per sec) and mechanical impact with turbine blades and have undergone over 1000 deployments.

Measuring sub-glacial flows. Water flowing in channels on the surface and inside a glacier changes how the glacier is moving but so far it has not been possible to measure. We send sensors into subglacial channels and measure acceleration, pressure and its rotation in magnetic field. After retrieval we analyse the data to extract information about the properties of subglacial channels.

Work in robot sensing has been funded by:

• FitHydro (Fishfriendly Innovative Technologies for Hydropower ) financed by European Commission through Horizon 2020 in 2016-2020

•  "Bioinspired Ecohydraulic Sensor Array for Laboratory and Insitu Flow Measurements” financed by Estonian Research Council ETAg grant PUT-1690 in 2017-2020.

DPSS (Differential Pressure Sensor Speedometer) is a novel device and method for measuring the flow speed with respect to an underwater vehicle. It can be used also on small and low-cost vehicles since it does not take much space and energy and does not cost much. Knowing your own speed is important for underwater robots because it helps them to estimate where they are, plan their path and not get lost. GPS does not work underwater and the only way of knowing your position is by guessing using onboard sensors.

Video: DPSS sensor mounted on an underwater vehicle SPARUS II in Underwater Robotics Research Centre in University of Girona.

Work in robot sensing has been funded by:

• ROBOCADEMY (European Academy for Underwater Robotics) financed by European Commission through Framework 7 in 2014- 2018

• “Bioinspired Underwater Robots” financed by Estonian Research Agency grant IUT-339 in 2015-2020.

• EXCITE (Estonian Centre for Excellence of IT Research) financed by SA Archimedes 2017-2023.

We are developing cost-effective water quality monitoring modules for remote and hard to access areas. The water quality units are equipped with water parameter sensors (pH, temperature, salinity, ORP, DO) and are solar powered along with GSM based communication modules.

A grid of the water quality monitoring has been tested and deployed on the island state of Grenada in the Caribbean Sea, where the freshwater reserves are affected by tropical storms.
The development and production of the cabinets has been realized in cooperation with Flydog Solutions Ltd.

Water quality monitoring project in Grenada is financed by the Republic of Estonia