Description of the Technology to be Researched and Developed as Prototype: AquaeyeTM is an autonomous floating aquatic sensor platform with an adaptable payload to sense a range of parameters (environmental conditions, chemical and biological hazards) for a variety of applications such as alerting oil spills and toxic algal blooms in bathing waters, pollution and fuel spills in inland waterways, marinas, harbours, shipping lanes and coastal waters. Deployed at the water-air interface tethered to buoys, maintenance, eventual recovery and re-purposing or re-location to address a new application are facilitated. Designed for disassembly-reassembly it is easily re-purposed. It is a small and low-cost (<£1000) device compared with the current state of the art devices, which are not designed for reuse/recycling and not autonomous (need to be secured in the monitoring medium). The AquaeyeTM has customisable data collection and transmission capability with cloud storage and data management, offering low-cost unmanned remote sensing capability with alerts to trigger emergency response e.g. chemical spills, toxic blooms or drinking water contamination for prompt mitigation. Current sensing ability includes in situ temperature, pH, oxidation-reduction potential & dissolved Oxygen.
This research will be focused on increasing the payload of the device with the PhD student further developing the device as follows:
- Apply BS8887 & ISO14006 to improve the design of the platform to accommodate more sensors, that is waterproof, buoyant, self-righting and recyclable
- Research additional power demand and innovate current PV-derived energy conversion & storage
- Develop PID sensors for oil spills, PAHs and colorimetric sensor for nitrates, phosphates, antibiotics, algal toxins
- Adapt existing circuits, data collection and transmission to accommodate the additional sensing capability.
Eligibility Criteria: Must have an undergraduate degree in an Engineering Discipline ideal with Mechanical and/or Electrical - Electronic Engineering knowledge.
Please tell us about previous lab and field experience and include a list of your modules taken and respective marks in your CV (especially for your past project/dissertation modules). Training will be provided but you are expected to have some relevant skills in programming Arduino and Raspberry Pie, CAD use and basic electronic circuits.