Towards the development of Intelligent Pedestrian Mobility Systems (IPMS)

Papageorgiou, George; Maimaris, Athanasios

doi:10.1109/iceltics.2017.8253267

Cited by 23 publications

(5 citation statements)

References 24 publications

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“…Data collecting has grown to be a major concern as digitization has per-edited daily life [9]. A broad, mobile, networked infrastructure is necessary for every smart city program to collect data.…”

Section: Figure 1 Construction Of the Prospective Smart Transportatio...mentioning

confidence: 99%

On-demand route allocation: A smart transportation scheme

Md Shadman Sakib Showrov,

Md Riaz Ahmad Shuvo,

Mohammad Yeasin Newaj Khan

et al. 2023

Int. J. Sci. Res. Arch.

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For effective crowd mobility, smart cities must have smart transportation. Smart cities need a transportation system that is intelligent, simple, and effective. Here is a creative idea for modernizing the current public transit system. Hardware modules based on the Internet of Things (IoT) that are required for implementation are discussed in this work. Traffic circumstances and extra elements have been added to Dijkstra’s shortest path method. The proposed algorithm has been tested in a number of circumstances, and the outcomes have been displayed accordingly. At a cheaper cost, the suggested solution can upgrade the current infrastructure. With various request counts, the algorithm performs well.

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Section: Figure 1 Construction Of the Prospective Smart Transportatio...mentioning

confidence: 99%

On-demand route allocation: A smart transportation scheme

Md Shadman Sakib Showrov,

Md Riaz Ahmad Shuvo,

Mohammad Yeasin Newaj Khan

et al. 2023

Int. J. Sci. Res. Arch.

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show abstract

“…Other methods, including machine learning (including clustering approaches) and identifying patterns in energy consumption, have been used to assist energy management systems in understanding the variation in household routines [47][48][49][50]. Additionally, other research has highlighted the potential of education and changing individuals' attitudes and mindsets to achieve energy savings [51,52]. However, achieving long-term behavioural changes is difficult, with many individuals reverting to their previous behaviours [32].…”

Section: Energy Managementmentioning

confidence: 99%

Identifying Home System of Practices for Energy Use with K-Means Clustering Techniques

Malatesta

Breadsell

2022

Sustainability

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Human behaviour is a major driver and determinant of household energy consumption, with routines and practices shaping daily energy profiles. These routines and practices are made up of individual lifestyles and other contextual factors that vary from home to home. Social and psychological theories aim to explain and describe how people consume resources in the home, which has resulted in the development of the home system of practice. This evaluates how occupants live and follow multiple routines which result in varying energy consumption practices. This paper develops a methodology to identify and support the concept of the home system of practice using a data analytical approach and link it to residential energy and distribution network management. This paper utilises k-means cluster analysis to identify these different home systems of practices and routines in energy use by using real-time energy consumption data from July 2019 to March 2021 from a living laboratory in Australia. The results of the analysis show the different daily energy profiles for each of the 39 households, with some homes observing large fluctuations and changes in the way they consume energy during the day. Specific homes were discussed as case studies in this paper focusing on linking the occupants’ contextual factors to their energy profiles. This variation is discussed in terms of the routines of the occupants and associated lifestyles that explain why some energy peaks occurred at different parts of the day and differed during the COVID-19 lockdown period in Australia. The paper conducts a comparison between these case studies to show how people’s lifestyles impact household energy consumption (and variation). These case studies investigated the heating and cooling practices of the occupants to demonstrate how they impact overall consumption. This variation is discussed in relation to energy management and prediction of when homes will consume energy to assist in net-zero energy developments and grid stabilisation operations.

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“…For that reason, the project sustains that implementing a Smart Pedestrian Network also requires developing technological tools, such as pedestrian navigation tools, to aid people to walk and to show the benefits of walking. There are many navigations systems in the market but they mainly address the needs of vehicle users and do not take into account the conditions provided to pedestrians [60]. Thus, a pedestrian navigation system running on mobile devices, such as smartphones, are particularly useful for providing navigational aid to users at unfamiliar places and additional data related to their trips (tracing the routes, obtaining health data, etc.).…”

Section: Roadmap For S Smart Pedestrian Network: Smart Pedestrian Assmentioning

confidence: 99%

Smart Pedestrian Network: An Integrated Conceptual Model for Improving Walkability

Fonseca

Ribeiro

Jabbari

et al. 2020

Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Smart and sustainable mobility have recently emerged as a solution to the problems incurred by the intensive use of motorised transport modes. For many decades, cities have been planned based on the needs of vehicle traffic, neglecting basic human needs for active mobility and the adverse effects of motorised traffic on the natural environment. However, walking is an environmentally friendly transport mode and a healthy form of making physical activity. Thus, walking becomes an essential component of the transport and urban policies for achieving a more sustainable development process. This paper presents the research project Smart Pedestrian Network (SPN) that aims at promoting walkability as one of the critical dimensions of smart and sustainable mobility in cities. The paper analyses the various components linked to SPN that can make a pedestrian network "smart" and, therefore, a feasible alternative to motorised transport modes. Three integrated components are analysed: i) an urban planning component supported in a GIS-based multi-criteria model to assess the conditions provided to pedestrians and to support the adoption of planning policies; ii) a smartphone app for pedestrian navigation, displaying optional routes according to the pedestrian preferences and needs; and iii) a business component to estimate and disseminate the multiple benefits of walking as well as the market potential of SPN. By promoting an innovative linkage of these three components, SPN has a great potential for improving walkability and, therefore, for creating more sustainable and liveable urban spaces.

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Towards the development of Intelligent Pedestrian Mobility Systems (IPMS)

Cited by 23 publications

References 24 publications

On-demand route allocation: A smart transportation scheme

On-demand route allocation: A smart transportation scheme

Identifying Home System of Practices for Energy Use with K-Means Clustering Techniques

Smart Pedestrian Network: An Integrated Conceptual Model for Improving Walkability

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