Renewable Energy Communities (RECs) are increasingly recognized as decentralized energy systems capable of improving renewable energy integration, enhancing local self-consumption, and supporting the transition toward low-carbon energy infrastructures. However, the effective deployment of RECs still faces significant challenges related to the integration of spatial analysis, energy modelling, operational optimization, and socio-economic assessment within a unified framework. This study investigates an integrated multi-objective framework for the design, evaluation, and operational support of RECs through the combination of geospatial analysis, energy performance modelling, and digital decision-support tools developed within the ENEA Smart Energy Communities (SEC) platform. The proposed methodology was developed by integrating spatially explicit territorial datasets, renewable resource assessments, electricity demand profiles, and multidimensional key performance indicators (KPIs) within a coordinated analytical framework. Three complementary tools were implemented and evaluated: the geoCER geoportal for territorial-scale renewable energy planning and REC scenario modelling, the DHOMUS platform for residential load monitoring and self-consumption optimization, and the Local Token Economy (LTE) system for token-based user engagement and energy-aware behavioral incentives. The results showed that the integrated framework effectively supported the assessment of REC configurations under different territorial and operational conditions. In the Anguillara Sabazia case study, the REC configuration increased the Self-Consumption Index (SCI) from 30% to 65% and the Self-Sufficiency Index from 36% to 79%, while reducing the Energy Surplus Index from 70% to 35%. In the Sardinia case study, the scenario-based analysis demonstrated that renewable energy integration and coordinated energy sharing significantly improved territorial self-sufficiency under optimized REC configurations. The geospatial modelling approach also enabled the identification of suitable renewable deployment scenarios while considering environmental and territorial constraints. The results indicate that the integration of energy modelling, digital monitoring systems, and spatially explicit planning tools provides an effective pathway for improving the operational performance, flexibility, and scalability of RECs. The proposed framework offers practical support for decentralized energy planning, distributed renewable energy management, and data-driven decision-making processes in future community-based energy systems.

This study addresses the growing role of Renewable Energy Communities (RECs) in supporting decentralized renewable energy integration and improving local energy self-sufficiency within the European energy transition framework. The work aimed to evaluate the technical and economic feasibility of a municipal REC in Pattada, a small municipality located in Sardinia, Italy, through an energy balance analysis based on distributed photovoltaic generation and shared electricity consumption. A techno-economic assessment framework was developed by combining the estimated electricity production of municipally owned photovoltaic systems with the load profiles of municipal, commercial, and residential users participating in the REC. The photovoltaic energy production was estimated using the Photovoltaic Geographical Information System (PVGIS) simulation platform, while the shared energy within the REC was evaluated by considering the simultaneity between electricity generation and demand under different residential participation scenarios. The results showed that the municipal photovoltaic systems achieved an annual electricity production of approximately 506.41 MWh, while direct physical self-consumption remained limited to 3.10 MWh/year due to the mismatch between municipal demand and photovoltaic generation profiles. The analysis further showed that the REC reached an energy equilibrium condition with the participation of 285 residential users, corresponding to nearly 23% of the households within the municipality, allowing virtually shared energy to reach 425.92 MWh/year. The economic evaluation demonstrated that the municipal administration obtained the highest share of the overall economic return, mainly driven by electricity exported to the grid and incentive revenues associated with shared energy. The results indicate that the integration of municipally owned photovoltaic systems within REC configurations provides an effective approach for improving local energy sharing and enhancing the economic viability of distributed renewable energy systems in small municipalities. The proposed framework offers practical support for local administrations in planning renewable energy investments and optimizing REC configurations under real operating conditions.

Sawahlunto City is highly vulnerable to landslides due to steep topography, unstable soil conditions, and the legacy of former mining activities. These conditions pose risks not only to settlements and infrastructure but also to environmental sustainability. This study aims to analyze local government strategies in landslide disaster mitigation using James Brian Quinn’s strategic framework, focusing on goals, policies, and programs. This research employs a qualitative approach with data collected through interviews, observation, and document analysis. This study involved 15 key informants selected through purposive sampling, consisting of Regional Disaster Management Agency (Badan Penanggulangan Bencana Daerah, BPBD) officials, regional apparatus organizations, and local government representatives. Additional triangulation was conducted with community-based and external actors such as Disaster Resilient Village (Desa Tangguh Bencana, Destana), Disaster Preparedness Cadets (Taruna Siaga Bencana, Tagana), Tsunami Alert Community (Komunitas Siaga Tsunami, KOGAMI), Jemari Sakato, and BPBD of West Sumatra Province. Data were collected between December 2024 and January 2025 through interviews, field observations, and document analysis, and analyzed using data reduction, categorization, and thematic interpretation based on strategic dimensions. The findings indicate that although BPBD Sawahlunto has established strategic planning documents such as Disaster Risk Assessment (Kajian Risiko Bencana, KRB), Disaster Management Plan (Rencana Penanggulangan Bencana, RPB), and Contingency Plans (Rencana Kontinjensi, Recon), their implementation remains constrained by limited budget and human resources. Programs such as Destana and Disaster Safe Education Unit (Satuan Pendidikan Aman Bencana, SPAB) contribute positively to community preparedness, although their coverage is still limited. The study concludes that strengthening inter-agency coordination, optimizing resources, and enhancing community participation are essential to improve the effectiveness and sustainability of landslide mitigation strategies in Sawahlunto City.

Tourism provides considerable economic advantages; however, it also imposes environmental challenges, especially in coastal regions where unmanaged waste poses a threat to long-term sustainability. This research seeks to examine the behavioral and spatial elements that affect tourists’ willingness to pay (WTP) for circular waste management in eight coastal destinations in Southern Yogyakarta, Indonesia. Employing the Contingent Valuation Method (CVM), primary survey data were gathered from 984 visitors and analyzed using Ordinary Least Squares (OLS) regression, K-Means clustering, and spatial mapping techniques with geomap orange data mining. The analysis investigates how socio-economic factors such as age, income, gender, education level, and travel costs influence WTP, with behavioral theory serving as the interpretive framework. The findings indicate that younger and more educated tourists demonstrate a higher WTP, while age and travel costs negatively and significantly impact their WTP. The estimated average WTP of IDR 13,840 surpasses the official waste retribution fee, reflecting a considerable level of environmental concern among visitors. Additionally, spatial and cluster analyses uncover diversity in visitor segments across coastal areas, implying that standardized waste management policies may not be effective. In summary, the results underscore the necessity of merging economic valuation with spatially informed and behaviorally conscious policy tools, illustrating the potential of WTP as a funding mechanism for sustainable and circular waste management in coastal tourism regions.

This study aims to analyze the traffic noise levels at three locations in Makassar City and to compare them with the established noise quality standards. Measurements were conducted over a one-week period at specific times using a sound level meter, a vehicle speed measurement device, and a counting application to classify vehicle types into heavy vehicles (HV), light vehicles (LV), and motorcycles (MC). The observation sites included an educational area, a hospital area, and a residential area. Correlation analysis using Statistical Package for the Social Sciences (SPSS) was employed to examine the relationships between HV, LV, MC, and vehicle speed with the equivalent continuous sound level (Leq). The results indicated that noise levels at all three locations exceeded the standard threshold of 55 decibels (dB). The correlation analysis showed significant relationships between Leq and HV (0.834), LV (0.782), MC (0.787), and vehicle speed (-0.680). The effective contribution to noise was highest for HV (40.44%), followed by MC (13.35%), LV (12.68%), vehicle speed (10.38%), and other factors (23.15%), including human activity, construction noise, road surface type, road gradient, and surrounding environmental conditions. Recommended mitigation measures include restricting the operating hours and rerouting of HV in sensitive areas, as well as enforcing noise emission testing and regulations on illegal exhaust modifications.

In mobility-aware scenarios such as vehicular networks, mobile augmented reality (AR)/virtual reality (VR) services, and other latency-sensitive Multi-access Edge Computing (MEC) applications, continuous user movement leads to frequent migrations of service function chains (SFCs). Traditional approaches typically rely on global deployment comparisons, which fail to accurately identify the specific virtual network functions (VNFs) that require migration and their optimal target nodes. This limitation often results in redundant migrations, inefficient resource utilization, and an increased risk of service disruption, thus hindering the balance between latency assurance and resource efficiency. To overcome these limitations, this paper proposed a graph-enhanced deep reinforcement learning–based adaptive migration optimization (DRL-GAMO) framework. By integrating the topological representation capability of graph neural networks (GNNs) with the decision-making efficiency of deep reinforcement learning (DRL), DRL-GAMO established a topology–resource–decision mapping that jointly optimized VNF selection and determination of target nodes. This pre-migration decision process effectively reduced redundant operations and directed migration behaviors toward resource-efficient strategies. The designed reward function minimized migration overhead under service-level agreement (SLA) latency constraints and penalized downtime to maintain service continuity. Simulation results demonstrated that DRL-GAMO achieved stable service latency, lower resource consumption, and shorter migration time while reducing migration volume by more than 40% compared with DRL-ADMO, thereby improving the migration success rate and validating its effectiveness in MEC environments.

The Public Utility Vehicle Modernization Program (PUVMP) is a key national reform in the Philippines’ mass transportation subsector. However, its application at the local level, island-provinces, has received limited attention. This study addresses that gap by evaluating Guimaras province’s Local Public Transport Route Plan (LPTRP). A questionnaire survey and transport modeling were used to assess travel behavior, accessibility, and network performance. Results show that many essential facilities, such as schools and health centers, are not adequately served by formal PUV routes. As a result, residents rely on informal modes that are often unsafe and expensive. The analysis also revealed issues with route overlap and inefficient area coverage. To address these local concerns, the study recommends redesigning routes, establishing transfer hubs, and adopting coordinated fleet management. These strategies aim to improve safety, accessibility, and system reliability for commuters. Overall, the findings offer a model for context-sensitive public transport planning in rural and island settings across the Philippines.