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Research Article
Smart Agriculture and Environmental Monitoring:
An Edge-AI, IoT, and Federated Learning Framework for Climate-Resilient Farming
Zarin Subha Progga
,
Mohammad Ali*
Issue:
Volume 10, Issue 4, December 2026
Pages:
112-123
Received:
6 September 2026
Accepted:
21 September 2026
Published:
9 October 2026
Abstract: This study presents a system architecture, algorithm, and evaluation protocol for smart agriculture and environmental monitoring. It is a method/architecture contribution and does not report field trial results. World food production is still under stress from climate variability, the availability of freshwater resources, and the cost of farm inputs, offering an incentive to transition to data-driven and sensor-based farm management practices. Internet of Things (IoT)-based agricultural monitoring is well developed, but most systems deployed focus on a single parameter (e.g., soil moisture) or the parameter is inferred solely in the cloud, adding latency and fragility to the deployment of systems in rural areas. In this study, we propose an integrated architecture for low-power multiparameter environmental sensing, LoRaWAN/NB-IoT connectivity, edge-based lightweight inference, and privacy-preserving federated learning with cross-farm model aggregation, which is further complemented by a digital twin layer for scenario simulation. The decision layer of the framework can combine data from ground sensors with UAV and satellite images for the multi-scale monitoring of crop health and environmental quality (air, water, and GHG proxies). We contribute the full system design, an algorithmic pipeline, a sensor and model configuration specification, and a pre-registered evaluation protocol intended to guide future field deployment; no field data have yet been collected and clearly labelled non-empirical templates showing the expected reporting format only, rather than measured outcomes. The architecture and protocol are instead grounded in, and cross-checked against, published state-of-the-art results, which report an accuracy range of 82–97% for federated crop-yield prediction and 20–30% water savings from sensor-controlled irrigation.
Abstract: This study presents a system architecture, algorithm, and evaluation protocol for smart agriculture and environmental monitoring. It is a method/architecture contribution and does not report field trial results. World food production is still under stress from climate variability, the availability of freshwater resources, and the cost of farm input...
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Research Article
Micro-Scale Environmental Justice: Community-Based Settlement Governance in RT 08/RW 04 Malaka Jaya, Jakarta, Under Indonesian Environmental Law
Taufiq Supriadi,
Sahat Parlindungan Simarmata*,
Ester Stefany Sahelangi,
Aliza Sakinah
Issue:
Volume 10, Issue 4, December 2026
Pages:
124-136
Received:
14 July 2026
Accepted:
23 September 2026
Published:
9 October 2026
Abstract: Dense urban settlements in Indonesia continue to face unequal access to green spaces, adequate sanitation, functional drainage systems, and proper waste management. This condition reflects issues of environmental justice, in which vulnerable groups disproportionately bear environmental risks due to high population density, limited land availability, and weak local governance. Although the principle of environmental justice has a constitutional basis in Article 28H of the 1945 Constitution and Law No. 32 of 2009, its implementation at the micro level—particularly at the Neighborhood Association (Rukun Tetangga/RT) level—remains rarely examined analytically. This study aims to analyze the extent to which community-based governance in RT 08/RW 04, Malaka Jaya Sub-district, Duren Sawit District, East Jakarta, realizes the distributive, procedural, and recognition dimensions of environmental justice, and to identify enabling and constraining factors. The research employs a descriptive qualitative case study approach using participatory observation, in-depth semi-structured interviews with seven key informants, and documentation of RT Online data and relevant regulations. Data were analyzed thematically based on the three-dimensional environmental justice framework, supported by source and method triangulation. All three dimensions of environmental justice were reflected through relatively equitable distribution of green facilities, collective participation in drainage and waste management, and recognition of residents' local knowledge. Structural risks such as density, limited land, and flood history were mitigated through inclusive leadership, technology-based data transparency, and multi-stakeholder collaboration. However, participation gaps and limitations in macro-level drainage infrastructure remain challenges. This study contributes conceptually and practically by offering an analytical model of RT-level governance grounded in environmental justice, adaptable to other dense urban settlements, and highlighting the need to formalize participatory mechanisms and data transparency at the sub-district and district levels.
Abstract: Dense urban settlements in Indonesia continue to face unequal access to green spaces, adequate sanitation, functional drainage systems, and proper waste management. This condition reflects issues of environmental justice, in which vulnerable groups disproportionately bear environmental risks due to high population density, limited land availability...
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Research Article
Understanding Landslide Risk, Building Resilience: Integrating Science, Policy, and Practice for Safer Communities: The Sierra Leone Experience
Edwin Sam-Mbomah*
Issue:
Volume 10, Issue 4, December 2026
Pages:
137-142
Received:
5 September 2026
Accepted:
18 September 2026
Published:
20 October 2026
Abstract: Landslides are complex natural hazards resulting from interactions among geological, geomorphological, hydrological, climatic and anthropogenic processes. In Sierra Leone, these risks are intensified by rapid urbanisation, environmental degradation, inadequate land-use planning and limited institutional capacity. The 14 August 2017 Regent landslide in the Freetown Peninsula demonstrated the severe consequences of rainfall triggered slope failure interacting with flooding, infrastructure vulnerability and human exposure. This study examines how landslide science, public policy and practical risk reduction measures can be integrated to promote safer and more resilient communities in Sierra Leone. It specifically considers the physical and human drivers of landslide risk, the contribution of inventories, susceptibility mapping, remote sensing, geospatial analysis and rainfall information, and the translation of scientific knowledge into planning, governance and community action. The paper adopts an integrated hazard-exposure-vulnerability-capacity framework and uses the Sierra Leone experience, particularly the Freetown Peninsula, as a case study. It synthesizes evidence from landslide inventories, susceptibility assessments, remote sensing studies, climate risk assessments, disaster risk policies and institutional developments. The analysis considers interactions among rainfall, terrain, land-use change, urbanisation, exposure, vulnerability and institutional capacity. The analysis shows that landslide risk in Sierra Leone is produced by the interaction of physical susceptibility and accumulated social vulnerability. The 2017 Regent event illustrates the importance of considering cascading processes, including landslide material, drainage networks, flood pathways and downstream exposure. Although scientific research, geospatial technologies and national disaster risk institutions are doing their utmost, gaps remain in risk communication, data management, community inclusion, infrastructure resilience and coordination between policy and implementation. Effective landslide risk reduction requires a shift from reactive disaster response towards integrated, anticipatory and community-centered resilience. Connecting geoscience, remote sensing, engineering, climate science, spatial planning, ecosystem management, governance and community knowledge can help ensure that scientific evidence directly informs development and risk reduction decisions.
Abstract: Landslides are complex natural hazards resulting from interactions among geological, geomorphological, hydrological, climatic and anthropogenic processes. In Sierra Leone, these risks are intensified by rapid urbanisation, environmental degradation, inadequate land-use planning and limited institutional capacity. The 14 August 2017 Regent landslide...
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