Earth Science Informatics, Journal Year: 2025, Volume and Issue: 18(2)
Published: Feb. 1, 2025
Language: Английский
Journal of Safety and Sustainability, Journal Year: 2025, Volume and Issue: unknown
Published: Feb. 1, 2025
Language: Английский
Citations
1
AI, Journal Year: 2025, Volume and Issue: 6(3), P. 44 - 44
Published: Feb. 21, 2025
Background: The adoption of artificial intelligence (AI) in public administration (PA) has the potential to enhance transparency, efficiency, and responsiveness, ultimately creating greater value. However, integration AI into PA faces challenges, including conceptual ambiguities limited knowledge practical applications. This study addresses these gaps by offering an overview categorization research applications PA. Methods: Using a dataset 3149 documents from Scopus database, this identifies top 200 most-cited articles based on citation per year. It conducts descriptive content analyses identify existing state, applications, challenges regarding adoption. Additionally, selected use cases European Commission’s database are categorized, focusing their contributions analysis centers three governance dimensions: internal processes, service delivery, policymaking. Results: findings provide categorized understanding concepts, types, PA, alongside discussion best practices challenges. Conclusion: serves as resource for researchers seeking comprehensive current state offers policymakers practitioners insights leveraging technologies improve delivery operational efficiency.
Language: Английский
Citations
1
International Journal of Disaster Risk Reduction, Journal Year: 2022, Volume and Issue: 84, P. 103470 - 103470
Published: Dec. 5, 2022
Language: Английский
Citations
38
Journal of Environmental Management, Journal Year: 2022, Volume and Issue: 312, P. 114939 - 114939
Published: March 23, 2022
Language: Английский
Citations
32
Sensors, Journal Year: 2022, Volume and Issue: 22(3), P. 1083 - 1083
Published: Jan. 30, 2022
Innovation in wireless communications and microtechnology has progressed day by day, this resulted the creation of sensor networks. This technology is utilised a variety settings, including battlefield surveillance, home security, healthcare monitoring, among others. However, since tiny batteries with very little power are used, target monitoring issues. With development various architectures algorithms, considerable research been done to address these problems. The adaptive learning automata algorithm (ALAA) scheduling machine method that study. It offers time-saving method. As result, each node network outfitted automata, allowing them choose their appropriate state at any given moment. one two states: active or sleep. Several experiments were conducted get findings suggested Different parameters experiment verify consistency for so it can cover all targets while using less power. experimental indicate proposed an effective approach schedule nodes monitor electricity. Finally, we have benchmarked our technique against LADSC algorithm. All data collected thus far demonstrate justified problem description achieved project's aim. Thus, constructing actual network, may be as useful nodes.
Language: Английский
Citations
29
IoT, Journal Year: 2024, Volume and Issue: 5(2), P. 250 - 270
Published: May 22, 2024
Smart agricultural drones for crop spraying are becoming popular worldwide. Research institutions, commercial companies, and government agencies investigating promoting the use of technologies in industry. This study presents a smart agriculture drone integrated with Internet Things that machine learning techniques such as TensorFlow Lite an EfficientDetLite1 model to identify objects from custom dataset trained on three classes, namely, pineapple, papaya, cabbage species, achieving inference time 91 ms. The system’s operation is characterised by its adaptability, offering two spray modes, modes A B corresponding 100% capacity 50% based real-time data, embodying potential monitoring autonomous decision-making. operated X500 development kit has payload 1.5 kg flight 25 min, travelling at velocity 7.5 m/s height 2.5 m. system aims improve sustainable farming practices optimising pesticide application improving health monitoring.
Language: Английский
Citations
6
ISPRS International Journal of Geo-Information, Journal Year: 2021, Volume and Issue: 10(8), P. 539 - 539
Published: Aug. 11, 2021
Global climate has been radically affected by the urbanization process in recent years. Karachi, Pakistan’s economic hub, is also showing signs of swift urbanization. Owing to construction infrastructure projects under China-Pakistan Economic Corridor (CPEC) and associated urbanization, Karachi’s significantly affected. The replacement natural surfaces anthropogenic materials results urban overheating increased local temperatures leading serious health issues higher air pollution. Thus, these temperature changes effects must be addressed minimize their impact on city’s population. For analyzing Karachi city, LST (land surface temperature) assessed current study, where data past 20 years (2000–2020) used. this purpose, remote sensing from Advanced Spaceborne Thermal Emission Reflection Radiometer Digital Elevation Model (ASTER GDEM) Moderate-Resolution Imaging Spectroradiometer (MODIS) sensors were utilized. long short-term memory (LSTM) model was utilized road density (RD), elevation, enhanced vegetation index (EVI) are used as input parameters. Upon comparing estimated measured LST, values mean absolute error (MAE), square (MSE), percentage (MAPE) 0.27 K, 0.237, 0.15% for January, 0.29 0.261, 0.13% May, respectively. low MAE, MSE, MAPE show a correlation between predicted observed values. Moreover, that more than 90% pixel falls least possible range −1 K +1 K. MSE Support Vector Regression (SVR) 0.52 0.453 0.18% 0.76 0.873, 0.26%. outperforms previous studies, shows accuracy, depicts greater reliability predict actual scenario. In future, based accurate model, city planners can propose mitigation strategies reduce harmful Urban Heat Island (UHI).
Language: Английский
Citations
37
Journal of the Indian Society of Remote Sensing, Journal Year: 2024, Volume and Issue: unknown
Published: Sept. 5, 2024
Language: Английский
Citations
5
Sustainability, Journal Year: 2021, Volume and Issue: 13(18), P. 10426 - 10426
Published: Sept. 18, 2021
Coronavirus Disease 2019 (COVID-19) has emerged as a global pandemic since late and affected all forms of human life economic developments. Various techniques are used to collect the infected patients’ sample, which carries risks transferring infection others. The current study proposes an AI-powered UAV-based sample collection procedure through self-collection kits delivery potential patients bringing samples back for testing. Using hypothetical case Islamabad, Pakistan, various test cases run where UAVs paths optimized using four key algorithms, greedy, intra-route, inter-route, tabu, save time reduce carbon emissions associated with alternate transportation methods. Four 30, 50, 100, 500 investigated delivering self-testing patients. results show that Tabu algorithm provides best-optimized covering 31.85, 51.35, 85, 349.15 km distance different numbers In addition, algorithms optimize number be in each address studied 5, 8, 14, 71 UAVs, respectively. first step towards practical handling COVID-19 other pandemics developing countries, spreading infections can minimized by reducing person-to-person contact. Furthermore, reduced footprints these added advantage countries struggle control such emissions. proposed system is equally applicable both developed help spread minimizing contact, thus helping transformation healthcare smart healthcare.
Language: Английский
Citations
29
Computer Communications, Journal Year: 2022, Volume and Issue: 190, P. 78 - 86
Published: April 18, 2022
Language: Английский
Citations
20