John Alexander Taborda Giraldo

Coastal oceanographic buoys provide high-frequency observations, but their scientific use requires channel-specific quality assessment and explicit treatment of representativeness. This study evaluates a coastal buoy deployed off Cabo de Gata, southeastern Spain, during two non-contiguous observation windows in 2025 and 2026. Buoy records were standardized, screened with quality-control tests, aggregated daily without gap filling, and compared with Copernicus Marine and ERA5 products as an external-consistency assessment. Gridded products were interpolated to the mean buoy position using inverse-distance weighting, and Copernicus Marine temperature was vertically interpolated to the 5 m and 10 m buoy-sensor depths. Completeness was 88.1–88.3% in 2025 and 99.9–100.0% in 2026, with no gross-range failures. Significant wave height and atmospheric pressure showed strong external consistency, with root mean square errors of 0.15/0.14 m and 0.63/0.59 hPa, respectively. Temperature at 5 m showed moderate-to-strong agreement, with errors of 0.98/0.64 °C. Wave-spectrum-derived wind speed showed larger, sea-state-dependent differences, although disagreement decreased under higher wave steepness. The workflow distinguishes channels suitable for daily environmental interpretation from those requiring additional metadata or independent field verification.

Life cycle assessment of photovoltaic systems still rests on aggregated, time-invariant inventories. In Colombia, where registered solar projects grew 128.6% between 2018–2022 and 2022–2025, environmental follow-up is self-reported, semi-annual and unmeasured by the authority. We report IMPACT Energy.CO, an infrastructure running in that authority’s production environment, which normalises heterogeneous sensor telemetry onto a versioned canonical vocabulary, hash-chains every derived indicator, and drives openLCA headlessly. A matrix of 144 candidate indicators was screened to 32 and scored independently by external experts and by communities in Magdalena and Cesar. On fifteen shared social indicators the two rankings show no detectable association (Spearman’s ρ = −0.07), yet their disagreement is ordered by stakeholder category: communities move an indicator up in priority the further its category lies from the firm’s internal sphere, and down the closer it lies (Kendall’s τ_b = 0.63, p = 0.004, utility-scale track). Experts rank labour conduct highest; communities rank their own channels of recourse highest. Of seventeen environmental indicators exactly two—energy and carbon payback time—cannot be obtained as impact-assessment results, because both are defined on measured generation; experts ranked them second and third. Harmonising IEA PVPS figures to Colombian irradiance lowers the mono-Si global warming potential by 32%, and carbon payback time varies three-fold across grid emission factors published for the same year. Static inventories cannot deliver the indicators their own users rank highest.

The transition toward decentralized renewable energy systems creates monitoring problems that current digital infrastructures do not solve: sustainability claims are produced by the same actors they evaluate, environmental evidence is reported periodically rather than observed continuously, and the communities most affected by deployment cannot inspect the data used to represent their territories. Existing integrated platforms combine subsets of the blockchain, Internet of Things (IoT) sensing and life cycle assessment (LCA) at the data layer, but they do not organize that integration through an explicit governance structure. This paper contributes a cybernetic governance framework in which the Viable System Model (VSM) supplies the organizing structure of a blockchain–IoT–LCA monitoring architecture, so that sensing, distributed trust, strategic intelligence and participatory governance are recursively coupled rather than sequentially chained. The framework was developed and evaluated under the Design Science Research paradigm, and instantiated in the IMPACT Energy.CO platform across two technology routes, wind and solar, in La Guajira, Cesar, Atlántico and Magdalena, Colombia. Evaluation against six pre-declared criteria reports 45 executed test cases with a 100% pass rate, 90% unit and 87% integration code coverage, load tests up to 5000 concurrent users with zero errors and sub-second mean response, an operating hash-chained provenance layer issuing verifiable LCA certificates, 14 participatory validation workshops, 199 users trained and 166 technicians certified. We use traceability in a deliberately narrow sense throughout: the property whereby a committed record can be linked to the ingested data series, model version and computation that produced it, and its integrity and ordering checked by a party that does not trust the producer. It is provenance and integrity traceability from the point of ingestion onward, and it is not metrological traceability: the architecture cannot verify that an original sensor measurement corresponds to the physical quantity it purports to represent. We accordingly make explicit what the architecture does not guarantee: a ledger protects records after commitment but cannot certify measurement at the point of capture, and we present a threat model, a set of implemented controls and the residual risk that remains. This study contributes an architecture, a reproducible development and evaluation method, and a calibrated account of what verifiable environmental monitoring can and cannot deliver in contested Global-South territories.

This work presents a spatially regularized modelling framework for selecting IoT-enabled environmental monitoring nodes within smart-lighting infrastructures. The study does not claim novelty in CRITIC, TOPSIS, mixed-integer programming, or Voronoi tessellation as isolated methods. Instead, its contribution is the problem-specific formulation and validation of a node-selection workflow in which CRITIC-derived criterion weights and TOPSIS suitability scores are used as suitability coefficients in a binary location model, while spatial redundancy is controlled through a distance-threshold penalty. Candidate-level datasets were available for three mining-impacted municipalities in northern Colombia: Albania (70 candidates), Algarrobo (87 candidates), and La Jagua de Ibirico (76 candidates). The implementation uses a minimum separation threshold d0 = 100 m, corresponding to a practical microscale spacing criterion for public-lighting-based monitoring stations, and evaluates sensitivity to the regularization parameter λ. Compared with pure top-k TOPSIS selection, the spatially regularized solutions eliminate close-pair conflicts below 100 m and increase the minimum inter-node distance to approximately 101.2 m in Albania, 105.6 m in Algarrobo, and 100.6 m in La Jagua de Ibirico in the high-regularization MILP runs. Solver runs for the sparse linearized MILP reached zero optimality gap on the reported instances. Voronoi tessellation is then used as an interpretive coverage tool, not as evidence of mathematical novelty. Finally, the analysis of criterion-weight distributions is presented as exploratory and descriptive because of the limited number of main criterion groups.

La incorporación de tecnologías de Inteligencia Artificial de las Cosas (IAoT) en contextos rurales enfrenta barreras estructurales del modelo tradicional de transferencia tecnológica descendente, que ignora las racionalidades socioculturales y los saberes locales de las comunidades beneficiarias. Persiste un vacío metodológico: no existen protocolos validados empíricamente para la co-creación comunitaria en proyectos agrícolas de IAoT en América Latina. Este trabajo presenta el diseño, la implementación y la validación de un protocolo de co-creación fundamentado en la Investigación Acción Participativa (IAP), desarrollado en el proyecto AgroHub (BPIN 2024000100047) en cuatro municipios del Magdalena, Colombia. El protocolo se estructuró en cuatro fases secuenciales y retroalimentadas —diagnóstico territorial, co-diseño tecnológico, implementación comunitaria y evaluación formativa— y se aplicó con 23 organizaciones comunitarias mediante dos instrumentos validados, el Índice de Apropiación Tecnológica (IAT) y el Índice de Participación Comunitaria (IPC), junto con cinco herramientas de mediación intercultural y un gradiente transferencia-co-creación de cuatro niveles inspirado en la escalera de participación de Arnstein. Los resultados evidencian avances sostenidos en ambos índices y muestran que los protocolos de co-creación estructurados constituyen una alternativa replicable para la innovación social en contextos rurales latinoamericanos con brecha digital significativa.

Environmental governance in the Global South increasingly unfolds within complex socio-technical systems characterized by fragmented institutional capacities, distributed sensing infrastructures, and high socio-ecological uncertainty. In this context, Digital Twins have emerged as a promising paradigm for integrating cyber–physical systems with decision intelligence, yet most implementations remain limited to industrial optimization or urban infrastructure management. This article proposes an architectural framework for Digital Twins oriented toward environmental governance by integrating Artificial Intelligence of Things (AIoT), monitoring networks with complex systems modeling and cybernetic governance principles. Methodologically, the study combines conceptual development grounded in systems science and the Viable System Model (VSM) with an illustrative empirical case study from the Caribbean Mining Corridor in Colombia, where a distributed AIoT environmental monitoring network operates within the Hub Ambiental del Caribe initiative. The proposed architecture links real-time environmental sensing, predictive analytics, and recursive governance structures to enable anticipatory environmental decision-making. The results demonstrate how Digital Twin infrastructures can function as cybernetic platforms that transform fragmented environmental data into actionable decision intelligence across institutional levels. By embedding feedback mechanisms, open environmental data governance, and participatory monitoring capacities, the framework supports adaptive management in highly dynamic socio-ecological contexts. The study concludes that Digital Twins designed as governance infrastructures—rather than purely technical replicas—can significantly enhance environmental decision support systems and foster climate justice-oriented transitions in vulnerable territories of the Global South.

Just energy transitions in the Global South unfold under conditions of institutional fragmentation, fiscal constraints, and high socio-ecological turbulence, making governance capacity a critical bottleneck for effective decarbonization and climate justice. This study proposes the Cybernetic Environmental Hub (CEH) framework, which extends the Viable System Model (VSM) to sustainability governance by integrating AIoT-enabled environmental monitoring, Early Warning Systems, decentralized data governance, and justice-centered institutional design. Methodologically, the article is primarily a conceptual framework paper accompanied by an illustrative single-site qualitative case study designed to probe the plausibility and diagnostic utility of the proposed architecture rather than to generate statistical generalization. The research combines theoretical development with participatory territorial diagnostics in the Caribbean Mining Corridor, where socio-ecological challenges were collected through participatory innovation workshops, thematically coded, and mapped onto the five VSM subsystems to identify systemic “variety gaps.” The analysis indicates that fragmented operational initiatives coexist with weak meta-systemic coordination, limiting adaptive capacity in energy transition processes. The CEH architecture is proposed to address these deficiencies by embedding AIoT sensing, federated learning, blockchain-based coordination, and Early Warning Systems within recursive governance structures and is grounded in a real cyber-physical deployment of around 90 monitoring stations across Albania, La Jagua de Ibirico and Algarrobo. The study also introduces a Territorial Governance Maturity Model (H1–H3) to diagnose systemic learning capacities and transition readiness across technological, institutional, data governance, and justice dimensions. The findings suggest that cybernetic environmental hubs may function as socio-technical infrastructures supporting coordinated, adaptive, and justice-centered energy transitions in the Global South, while comparative empirical evidence remains an agenda for future work.

Oceanographic buoys are essential platforms for marine observation, supporting real-time monitoring, climate studies, operational oceanography, coastal management, and offshore activities. This review maps the scientific literature on oceanographic buoys and identifies the main research sectors that structure the field. A Scopus search using TITLE-ABS-KEY((oceanographic OR metocean OR “ocean observing” OR “ocean observation”) AND (buoy OR buoys)) retrieved 1876 documents published between 1938 and 2026. The records were processed using a network-based sector detection and visualization workflow. Five thematic sectors were identified: platform engineering, sensors, moorings, and autonomous systems; marine wind, waves, metocean, and offshore energy applications; physical oceanography, sea-surface temperature (SST), currents, and environmental variability; coastal and ocean observing networks and operational services; and drifting buoys, floats, and global ocean datasets. The results show that buoy research has evolved from isolated measurement systems to integrated observing infrastructures that combine in situ sensing, satellite validation, autonomous operation, telemetry, and decision-support services. By linking bibliometric structure and thematic interpretation, this review provides a sector-based map showing where scientific observation, engineering design, operational services, and autonomous technologies converge.