AquaQ2

System demonstrator for the acquisition, treatment and interpretation of water quality data and water resources collected in sensor network

Project Description aquaQ2

The AquaQ2 project is devoted to the design and implementation of a demonstration system for the recognition of water quality standards and quantity of water resources. The system is subdivided into the following subsystems: a pattern recognition subsystem, using deep learning techniques used in artificial intelligence, which provides the users with high-level processed information, obtained from continuously collected data and saved in a secure way coded as blockchain; a data aggregation subsystem using microcomputers commonly used in IoT (Internet of Things) for data collection and transmission; and a subsystem for the remote collection of signals from sensors, used for the acquisition of information on physical-chemical parameters of water quality and quantity.

Main Goals Development of a system that shows the application of IoT, artificial intelligence (deep learning) and blockchain (data security) in the area of water quality management and water resources.

Publications

2022

2021

2020

Almeida, C., Martins, J.C., Santos, J.M. and Caeiro, J.J. (2022) ‘Smart lysimeter with crop and environment monitoring’, in Camarinha-Matos, L.M., Heijenk, G., Katkoori, S., and Strous, L. (eds) Internet of things. Technology and applications. Cham: Springer International Publishing, pp. 48–63. doi:https://doi.org/10.1007/978-3-030-96466-5_4.
Caeiro, J.J. and Martins, J.C. (2021) ‘Water management for rural environments and IoT’, in Research anthology on blockchain technology in business, healthcare, education, and government. IGI Global, pp. 246–262. doi:10.4018/978-1-7998-5351-0.ch015.
Caeiro, J.J., Martins, J.C., Barbosa, D., Barraca, J.P., Gomes, D. and Maia, D. (2020) ‘Turning radioastronomy and future SKA infrastructure into an internet of things (IoT) system: Enabling smart farming and water quality monitoring’, in Portuguese SKA white book. UA Editora – Universidade de Aveiro, p. 137—148. Available at: http://hdl.handle.net/10773/28376.
Carvalho, R.S., Santos, J.M., Martins, J.C., Santos, J.F., Palma, P. and Caeiro, J.J. (2022) ‘Hydric resources and meteorological monitoring IoT system’, in Camarinha-Matos, L.M., Heijenk, G., Katkoori, S., and Strous, L. (eds) Internet of things. Technology and applications. Cham: Springer International Publishing, pp. 252–267. doi:https://doi.org/10.1007/978-3-030-96466-5_16.
Lameira, M.F., Martins, J.C., Santos, J.M. and Caeiro, J.J. (2022) ‘IOT MONITORING SYSTEM FOR IRRIGATION CANALS’, in Proceedings of the 3rd international conference in electronic engineering, information technology and education EEITE-2022, pp. 53–60.
Oliveira, G., Almeida, C., Santos, J.M., Martins, J.C. and Caeiro, J.J. (2022) ‘IoT lysimeter system with enhanced data security’, in Brito Palma, L., Neves-Silva, R., and Gomes, L. (eds) CONTROLO 2022. Cham: Springer International Publishing, pp. 119–129. doi:10.1007/978-3-031-10047-5_11.
Santos, J.M., Caeiro, J.J., Martins, J.C., Santos, J.F. and Palma, P. (2020) ‘Physical and chemical water quality parameters sensing IoT systems for improving water productivity’, Water Productivity Journal, 1(2), pp. 22–46. Available at: http://www.waterproductivity.net/article_125104.html.
Santos, J.M., Carvalho, R., Martins, J.C., Santos, J.F., Palma, P., Maia, D., Barraca, J.P., Gomes, D., Bergano, M., Barbosa, D. and Caeiro, J.J. (2021) ‘A smart IoT system for water monitoring and analysis’, in Smart objects and technologies for social good. Springer International Publishing, pp. 67–79. doi:10.1007/978-3-030-91421-9_6.
Santos, J.M., Martins, J.C. and Caeiro, J.J. (2022) ‘IOT LONG RANGE COMMUNICATION TECHNOLOGIES LoRa and LoRaWAN’, in Proceedings of the 3rd international conference in electronic engineering, information technology and education EEITE-2022, pp. 45–52.

Supervision

Carlos Manuel dos Santos Almeida,
"Lisímetro Inteligente com Monitorização da Cultura e Ambiente,"
MSc. in Internet of Things at the Instituto Politécnico de Beja
(28/03/2022)
Carlos Alexandre Rijo Palma,
"Monitorização da Qualidade da Água,"
MSc. in Computer Security Engineering at the Instituto Politécnico de Beja
(8/03/2022)
Raul Manuel Sousa Carvalho,
"Monitorização da Qualidade da Água,"
MSc. in Internet of Things at the Instituto Politécnico de Beja, 2022.
(20/01/2022)

Funding

2019-11 to 2021-05
Contract N/A (N/A, PT)
GRANT_NUMBER: ALT20-03-0145-FEDER-039494
Total funding amount: EUR 190,248

Laboratório SEPSI 2022