Impact of digitalization of public transport and city mobility on traffic structure and on-road emissions

Netov, Nikolay; Lomev, Boyan

doi:10.1109/elecs55825.2022.00019

Cited by 2 publications

References 19 publications

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Forecasting of the Event-driven Processes Using LSTM Network in the Context of Time of Arrival of On-demand City Transport

Marchev,

Lomev

2024

IOP Conf. Ser.: Mater. Sci. Eng.

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The precise forecasting of bus arrival times is an important element of implementing on demand city transport. This research uses of Long Short Term Memory (LSTM) networks for predicting bus arrival times in Sofia, Bulgaria. We evaluate the LSTM model against advanced models such as ARIMAX, VARX SARIMAX with Fourier terms Vector Autoregression, Bayesian Fourier models and Backpropagation Neural Networks using Root Mean Squared Error (RMSE) as the performance measure. The results points towards LSTM being better than approaches on routes by adeptly capturing intricate temporal relationships showcasing its promise in dynamic urban transit settings. Moreover the Bayesian Fourier model excels across routes underscoring its ability to accommodate trends effectively. These results suggest that incorporating LSTM networks into on demand transportation systems can notably enhance arrival time forecasts ultimately benefiting passengers and operational efficiency. This study demonstrates the usefulness of machine learning methods in urban transport planning and management by demonstrating how LSTM networks can improve optimization, on demand transportation.

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Forecasting of the Event-driven Processes Using LSTM Network in the Context of Time of Arrival of On-demand City Transport

Marchev,

Lomev

2024

IOP Conf. Ser.: Mater. Sci. Eng.

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Digital Marketing Strategies for Enhancing the Sustainable Attractiveness of Smart Cities in Morocco

Routabi,

Bennani

2024

Advances in Marketing, Customer Relationship Management, and E-Services

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This article explores the strategic role of digital marketing in enhancing the sustainable attractiveness of smart cities, with a specific focus on Casablanca, Morocco. By integrating digital technologies such as the Internet of Things (IoT), data analytics, and artificial intelligence, Casablanca aims to address urban challenges related to sustainability, including transportation, waste management, and energy efficiency. This study employs a mixed-method approach, combining qualitative interviews with urban planners and digital marketing experts, alongside quantitative analysis of smart city performance indicators. Five smart cities across different continents were selected to provide comprehensive insights and contextualize the findings for Casablanca. The results demonstrate that targeted digital marketing strategies, when well-implemented, play a crucial role in improving citizen engagement, environmental awareness, and resource optimization, while reinforcing Casablanca's position as a sustainable smart city in Africa.

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Impact of digitalization of public transport and city mobility on traffic structure and on-road emissions

Cited by 2 publications

References 19 publications

Forecasting of the Event-driven Processes Using LSTM Network in the Context of Time of Arrival of On-demand City Transport

Forecasting of the Event-driven Processes Using LSTM Network in the Context of Time of Arrival of On-demand City Transport

Digital Marketing Strategies for Enhancing the Sustainable Attractiveness of Smart Cities in Morocco

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