Thesis
Publications
2025
Evaluation of MQTT Bridge Architectures in a Cross-Organizational Context
Authors: Keila Lima, Tosin Daniel Oyetoyan, Rogardt Heldal, and Wilhelm Hasselbring
2025 IEEE 22nd International Conference on Software Architecture (ICSA)
The latest surveys estimate an increasing number of connected Internet-of-Things (IoT) devices (around 16 billion) despite the sector’s shortage of manufacturers. All these devices deployed into the wild will collect data to guide decision-making that can be made automatically by other systems, humans, or hybrid approaches. In this work, we conduct an initial investigation of benchmark configuration options for IoT Platforms that process data ingested by such devices in real-time using the MQTT protocol. We identified metrics and related MQTT configurable parameters in the system’s component deployment for an MQTT bridge architecture. For this purpose, we benchmark a real-world IoT platform’s operational data flow design to monitor the surrounding environment remotely. We consider the MQTT broker solution and the system’s real-time ingestion and bridge processing portion of the platform to be the system under test. In the benchmark, we investigate two architectural deployment options for the bridge component to gain insights into the latency and reliability of MQTT bridge deployments in which data is provided in a cross-organizational context. Our results indicate that the number of bridge components, MQTT packet sizes, and the topic name can impact the quality attributes in IoT architectures using MQTT protocol.
2024
A data-flow oriented software architecture for heterogeneous marine data streams
Authors: Keila Lima, Ngoc-Thanh Nguyen, Rogardt Heldal, Lars Michael Kristensen, Tosin Daniel Oyetoyan, Patrizio Pelliccione, and Eric Knauss
2024 IEEE 21st International Conference on Software Architecture (ICSA)
Marine in-situ data is collected by sensors mounted on fixed or mobile systems deployed into the ocean. This type of data is crucial both for the ocean industries and public authorities, e.g., for monitoring and forecasting the state of marine ecosystems and/or climate changes. Various public organizations have collected, managed, and openly shared in-situ marine data in the past decade. Recently, initiatives like the Ocean Decade Corporate Data Group have incentivized the sharing of marine data of public interest from private companies aiding in ocean management. However, there is no clear understanding of the impact of data quality in the engineering of systems, as well as on how to manage and exploit the collected data. In this paper, we propose main architectural decisions and a data flow-oriented component and connector view for marine in-situ data streams. Our results are based on a longitudinal empirical software engineering process, and driven by knowledge extracted from the experts in the marine domain from public and private organizations, and challenges identified in the literature. The proposed software architecture is instantiated and exemplified in a prototype implementation.
A modular smart ocean observatory for development of sensors, underwater communication and surveillance of environmental parameters
Authors: Øivind Bergh, Jean-Baptiste Danre, Kjetil Stensland, Keila Lima, Ngoc-Thanh Nguyen, Rogardt Heldal, Lars-Michael Kristensen, Tosin Daniel Oyetoyan, Inger Graves, Camilla Sætre, et al.
Sensors, 2024
2023
Engineering Challenges of Stationary Wireless Smart Ocean Observation Systems
Authors: Ngoc-Thanh Nguyen, Rogardt Heldal, Keila Lima, Tosin Daniel Oyetoyan, Patrizio Pelliccione, Lars Michael Kristensen, Kjetil Waldeland Hoydal, Pål Asle Reiersgaard, and Yngve Kvinnsland
IEEE Internet of Things Journal, 2023
The ocean is vital for humankind but may cause catastrophes when unhealthy. Although there have been efforts to build ocean monitoring systems, the understanding of the underwater environment is limited due to the cost and challenges of obtaining real-time marine data. One potential solution is to build stationary ocean observation systems based on wireless communication due to its affordable cost. In this study, we divide these systems into three components: 1) underwater data acquisition; 2) network communication; and 3) data management. We investigate the engineering challenges associated with each component, the causes, and how they relate. The literature has not discussed the technical issues of building stationary smart ocean monitoring systems entirely based on wireless communication yet. This article fills that research gap by conducting semi-structured interviews with 17 experts knowledgeable about underwater sensors, underwater acoustic communication, offshore network communication, and underwater data usage. The identified challenges are compared with the literature to assess whether our findings are novel or are a confirmation of what have been already found in prior publications. The Internet of Things (IoT) used in smart city platforms is quite advanced, but the Internet of Underwater Things (IoUT) employed in smart ocean monitoring systems has several unresolved issues; although IoT is viewed as a foundation for IoUT. Therefore, we compare fundamental differences between the technologies used in the smart city and the smart ocean domains, explaining why some of our identified challenges are unique in the marine context.
Synthesized data quality requirements and roadmap for improving reusability of in-situ marine data
Authors: Ngoc-Thanh Nguyen, Keila Lima, Astrid Marie Skålvik, Rogardt Heldal, Eric Knauss, Tosin Daniel Oyetoyan, Patrizio Pelliccione, and Camilla Sætre
2023 IEEE 31st International Requirements Engineering Conference (RE)
Background: In-situ marine data has a low reusability rate, primarily due to differences in data usage objectives among stakeholders in data ecosystems. The extreme cost of collecting and maintaining in-situ marine data threatens the sustainable usage of the ocean. Aims: This paper provides an overview of current data and data quality (DQ) requirements. We also investigate limitations in the current practices that obstruct data reusability. The ultimate objective is to improve data requirements elicitation, leading to enhanced data reusability. Method: We interviewed 14 marine practitioners and researchers from 7 organizations with extensive experience in collecting, managing, and utilizing in-situ marine data. Results: We identify 9 representative use cases in the fishery, energy, and marine sciences industries, as well as their data and DQ requirements. The results give guidance to data producers to produce data meeting demands of a wider range of data consumers. At the same time, data consumers can refer to the compilation to identify existing data suiting their needs. Furthermore, we recommend a roadmap taken into account during requirements elicitation to improve 6 limitations in the current practices that obstruct data reusability.
Towards a Formal and Executable Software Architecture Specification of the Smart Ocean Data Service Platform.
Authors: Rogardt Heldal, Lars Michael Kristensen, Keila Lima, Tosin Daniel Oyetoyan, Ngoc-Thanh Nguyen
PNSE’23: Workshop on Petri Nets and Software Engineering
We present the Coloured Petri Nets (CPNs) modelling of the SmartOcean platform currently under development and aimed at providing cloud-based services for data-driven software systems and applications relying on marine data. The CPN model captures the systems-of-system architecture and the platform services, and is intended to evolve as a formal foundation along-side the implementation of the platform and its services. The CPN model encompass data-, messaging-, security-, and edge integration services with a focus on providing an abstract modelling of the service and system interaction. As part of the modelling work, we provide some general CPN patterns for system-of-systems modelling and service provision, consumption, and interaction.
Marine Data Observability using KPIS: An MDSE Approach
Authors: Keila Lima, Ludovico Iovino, Maria Teresa Rossi, Rogardt Heldal, Tosin Daniel Oyetoyan, and Martina De Sanctis
2023 ACM/IEEE 26th International Conference on Model Driven Engineering Languages and Systems (MODELS)
The 2023 climate change report states that the current temperature rise has led to recurring and hazardous weather events, devastating communities and the planet. Ocean observation systems and marine data generated by them are crucial for predicting these extreme events, understanding the ecosystem states, and regulating marine industries. Many regional and global initiatives have been supporting the collection and sharing of more data, filling gaps in ocean observation. However, some challenges can impact the quality of marine data at different points of data delivery pipelines: from acquisition and transmission at the Internet-of-Underwater-Things (IoUT) level up to storage and sharing. IoUT devices can have challenges due to limited battery, rough underwater terrain, error-prone wireless underwater communication, or low communication bandwidth to the cloud. Thus, mechanisms must be put in place to allow monitoring of data quality throughout the delivery pipeline, to optimize the usage of data and improve decision-making based on the data. This study explores observation of marine data quality on a data platform using Key Performance Indicators (KPIs). We have created a model of the platform and specified KPIs. Both are fulfilled by platform-collected data quality metrics, with the purpose to infer the state of the data in the platform over different periods. Our results show that the model-based implementation is able to function as a semantic translator between a metric monitoring toolkit and the platform objectives, integrating it into an observable subsystem for the overall middleware data platform.
2022
Marine data sharing: Challenges, technology drivers and quality attributes
Best Paper Award
Authors: Keila Lima, Ngoc-Thanh Nguyen, Rogardt Heldal, Eric Knauss, Tosin Daniel Oyetoyan, Patrizio Pelliccione, and Lars Michael Kristensen
2022 Product-Focused Software Process Improvement (PROFES)
Coordinated robotic exploration of dynamic open ocean phenomena
Authors: Jose Pinto, Maria Costa, Renato Mendes, Keila Lima, Paulo Dias, João Pereira, Manuel Ribeiro, Renato Campos, Maria Paola Tomasino, Catarina Magalhães, Francisco López Castejón, Francisco Javier Lucas Gilabert Cervera, Adriana Santos Ferreira, José CB da Silva, Paulo Relvas, Trent Lukaczyk, Kay Arne Skarpnes, Emilyn Davies, Alexander Chekalyuk, Bruno Loureiro, Ian G Brosnan, Jing Li, João Borges de Sousa, and Kanna Rajan
The study of dynamic features of the ocean, in which complex physical, chemical, and biological interactions evolve on multiple time scales, poses significant sampling challenges because the required spatial and temporal resolutions are not possible by ship or satellite studies alone. Satellite remote sensing captures only surface effects while expensive research vessels can only make discrete observations in finite periods of time. Our work with networked marine robotics in the aerial, surface, and underwater domains is at the vanguard of a new approach to scientific exploration and observation, which brings together several technologies to enable oceanographic vessels and robots to work in tandem, thus expanding the observational footprint of these vessels. We describe a scientific cruise in the Spring of 2018 in the open waters of the Pacific where we deployed a fleet of autonomous robots to demonstrate this approach for the synoptic observation of mesoscale and sub-mesoscale features of a frontal zone. We articulate the elements and methods to multi-vehicle coordination and challenges that lie ahead in ocean observation.
2021
Optimal AUV trajectory planning and execution control for maritime pollution incident response
Authors: Alexandre Rocha, Miguel Aguiar, Keila Lima, Renato Mendes, João M Dias, Magda C Sousa, and João Borges De Sousa
2021 OCEANS - MTS/IEEE San Diego–Porto (OTO)
Marine pollution incidents can have a huge impact on different ecosystems, with unpredictable short- and long-term consequences. Once the pollutant is detected, it is critical to quickly understand its characteristics so that authorities can lay out an adequate response. In parallel to the time- and cost-constrained traditional operational means, this paper suggests the use of AUVs for the sampling procedures of marine pollution incidents, to increase the speed and efficiency of operations. A new software architecture is developed, integrating trajectory optimization for AUVs into a software toolchain that allows human operators to plan, simulate, and control multiple vehicles deployments. A method to optimize AUVs deployment position and time is also presented. The overall architecture is simulated using high-resolution hydrodynamic data from the Ria de Aveiro lagoon and the adjacent coastal area, in Aveiro, Portugal.
2020
To boldly dive where no one has gone before: Experiments in coordinated robotic ocean exploration
Authors: José Pinto, Maria Costa, Keila Lima, Paulo Dias, João Pereira Manuel Ribeiro, Renato Campos, Zara Mirmalek, Renato Mendes, Francisco López Castejón, Javier Gilabert, Maria Paola Tomasino, Catarina Magalhães, José CB da Silva, Paulo Relvas, Trent Lukaczyk, Kay Arne Skarpnes, Martin Ludvigsen, Alexander Chekalyuk, Bruno Loureiro, Ian G Brosnan, Jing Li, Ami Hannon, João Borges de Sousa, and Kanna Rajan
Study of ocean processes is important to understanding climatic variability especially on the productive upper water-column. Ocean currents regulate the climate, it captures CO from the atmosphere and oxygen is generated by its plankton communities, all of which are part of the global environmental cycle which are being impacted by anthropogenic change. Much of the ocean, however, remains unexplored especially the bio-geochemical processes in the water-column which need to be examined at scale. Satellite remote sensing captures only surface effects while expensive research vessels can only make discrete observations in finite periods of time. Our work with networked marine robotics in the aerial, surface and underwater domains is at the vanguard of a new approach to scientific observation, which brings together technology to enable vessels and robots to work in tandem for capturing synoptic views of open ocean phenomena. We describe a cruise in the Spring of 2018 in the open waters of the Pacific where we employed a fleet of autonomous robots for simultaneous observations of mesoscale and sub-mesoscale features of an unexplored frontal zone. We articulate our approach to multi-vehicle coordination and challenges that lie ahead for research in this harsh domain.
Large Scale Unmanned Vehicles Oceanic Exercise REP (MUS) 19 Field Report
Authors: Paulo Sousa Dias, Maria Costa, José Pinto, Keila Lima, Luís Venâncio, Miguel Aguiar, and João Borges Sousa
2020 IEEE/OES Autonomous Underwater Vehicles Symposium (AUV)(50043)
The REP(MUS)19 is an exercise that takes place annually since 2010 in the south of continental Portugal. LSTS (Under-water Systems and Technology Laboratory) has co-organized these events, since the beginning, together with the Portuguese Navy and, in more recent years, with NATO-CMRE. NATO's MUS (Maritime Unmanned Systems Initiative) initiative joined the event in 2019. The target of these exercises is to have technological experimentation activities that engage armed forces, universities, and industry, in the unmanned system's operation. The event operational environment enables interactions between all parties to share experiences and needs to drive research in the direction of real-life needs. LSTS' participation in the 2019 event consisted of eight exercises.
Cross-Domain command and communications synergies towards more effective cooperative missions
Authors: Paulo Dias, Michael Incze, Keila Lima, Maria Costa, Manuel Ribeiro, Joao Tasso Borges de Sousa, Joshua Baghdady, Ben Jones, Noah Hafner, A Zachary Trimble, Raymond Andrade, and Margo Edwards
Ocean Sciences Meeting 2020, American Geophysical Union
2019
Underwater archaeology with light auvs
Authors: Maria Costa, José Pinto, Manuel Ribeiro, Keila Lima, Alexandre Monteiro, Peter Kowalczyk, and João Sousa
2019 OCEANS - MTS/IEEE Marseille Techno-Oceans (OTO)
For millennia, ships were lost at sea leading to the loss of an estimated 3 million vessels. This paper describes a light autonomous underwater vehicle specially tailored for coastal archaeology applications where a big part of this heritage sites should be found. This specific vehicle includes sonars, an optical camera and a magnetometer to detect and identify archaeological artifacts in the ocean bottom or underneath. It can be used isolated or as part of a team of AUVs for faster surveys. We describe the hardware, its simplified operation using custom-made software and overview some results in different areas, where these vehicles have been used to detect several wrecks and other important artifacts.
Comprehensive habitat mapping of a littoral marine park
Authors: Keila Lima, José Pinto, Vasco Ferreira, Bárbara Ferreira, André Diegues, Manuel Ribeiro, and João Borges de Sousa
OCEANS 2019-Marseille
Marine Protected Areas classification can help in the protection and monitoring of important ecosystems that might be sheltered by their habitats.New instrumentation techniques are being applied to study this type of environments, performing various scientific surveys in the water. In this paper we introduce a practical approach for habitat mapping, from the surface through the seabed, using autonomous underwater and unmanned aerial vehicles. We address high-resolution characterization of extensive coastal areas in challenging conditions by deploying multiple vehicles simultaneously. This approach has been applied in the field, to map a large coastal area, contouring the area intrinsic challenges by using a robust software toolchain developed to operate these vehicles, from planning and execution to the data analysis stages.
2018
Dolphin: a task orchestration language for autonomous vehicle networks
Authors: Keila Lima, Eduardo RB Marques, José Pinto, and Joao B Sousa
2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
We present Dolphin, an extensible programming language for autonomous vehicle networks. A Dolphin program expresses an orchestrated execution of tasks defined compositionally for multiple vehicles. Building upon the base case of elementary one-vehicle tasks, the built-in operators include support for composing tasks in several forms, for instance according to concurrent, sequential, or event-based task flow. The language is implemented as a Groovy DSL, facilitating extension and integration with external software packages, in particular robotic toolkits. The paper describes the Dolphin language, its integration with an open-source toolchain for autonomous vehicles, and results from field tests using unmanned underwater vehicles (UUVs) and unmanned aerial vehicles (UAVs).
Field report: Exploring fronts with multiple robots
Authors: Maria Joao Costa, José Pinto Paulo Sousa Dias, Joao Pereira, Keila Lima, Manuel Ribeiro, Joao Borges Sousa, Trent Lukaczyk, Renato Mendes, Maria P Tomasino, Catarina Magalhaes, Igor Belkin, Francisco Lopez-Castejon, Javier Gilabert, Kay Skarpnes, Martin Ludvigsen, Kanna Rajan, Zara Mirmalek, and Alex Chekalyuk
2018 IEEE/OES Autonomous Underwater Vehicle Workshop (AUV)
This paper presents a report from a cruise onboard the R/V Falkor oceanographic vessel from the Schmidt Ocean Institute. The goal of this cruise was to demonstrate a novel approach to observe the ocean with multiple underwater, surface, and aerial vehicles, as well with the R/V Falkor also used as the base and control center for all assets. We describe the planning phase leading up to the cruise, the technical approach, developments and timeline of results and decisions made throughout the cruise.Our approach combines a set of new technologies that enabled scientists and engineers to obtain a synoptic view of the study area, with adjustable spatial and temporal resolution, and to compare data collected in near real-time to the outputs of computational models. This approach was applied to map the Pacific Ocean's Subtropical front with unprecedented spatial and temporal resolutions.
Programming Networked Vehicle Systems Using Dolphin-Field Tests at REP'17
Authors: Keila Lima, Eduardo RB Marques, José Pinto, Joao B Sousa
2018 OCEANS-MTS/IEEE Kobe Techno-Oceans (OTO)
The increasing availability and use of autonomous vehicles for real operational scenarios has led to the need for tools that allow human operators to interact with multiple systems effectively, taking into account their capabilities, limitations and environmental constraints. Multiple vehicles, deployed together in order to accomplish a common goal, impose a high burden on a human operator for specifying and executing coordinated behavior, particularly in mixed-initiative systems where humans are part of the control loop. In this paper, we describe experimental field tests for Dolphin, a domain-specific language that allows a single program to define the joint behaviour of multiple vehicles over a network. Using the language, it is possible to accomplish an orchestrated execution of single-vehicle tasks according to several patterns such as sequential, concurrent, or event-based program flow. With this aim, Dolphin has been integrated modularly with a software toolchain for autonomous vehicles developed by Laboratório de Sistemas e Tecnologia Subaquática (LSTS). The tests we describe made use of LSTS unmanned underwater vehicles (UUVs) at open sea during the 2017 edition of Rapid Environment Picture (REP), an annual exercise jointly organised by LSTS and the Portuguese Navy.
Characterization of highly dynamic coastal environments, employing teams of heterogeneous vehicles: A holistic case study
Authors: Tiago Marques, Keila Lima, Manuel Ribeiro, António Sérgio Ferreira, João Borges Sousa, and Renato Mendes
2018 OCEANS - MTS/IEEE Kobe Techno-Oceans (OTO)
Collecting, analyzing and characterizing data from highly dynamic oceanic environments can be logistically taxing and costly, specially when done over long intervals of time using traditional manned methods. This usually discourages attempts at obtaining data of high spatial and temporal resolution. Nevertheless, through the use of teams of networked autonomous vehicles, these costs can be reduced and data collection and post-processing methods can be ameliorated. The work presented follows multi-vehicle operational scenarios, in a coastal environment, during large scale joint venture exercise with the Portuguese Navy, with the intent of collecting high spatio-temporal resolution data, over the course of a 2 week campaign, yielding promising results.
