[et_pb_section fb_built=”1″ fullwidth=”on” admin_label=”Hero Section” _builder_version=”4.27.4″ background_color=”#0e24ea” background_image=”https:\/\/www.go-mobility.it\/wp-content\/uploads\/work-mobility-data.jpg” background_position=”bottom_right” background_horizontal_offset=”0%” background_vertical_offset=”26%” background_blend=”multiply” min_height=”250px” height=”250px” max_height=”250px” custom_padding=”|||” global_colors_info=”{}”][\/et_pb_section][et_pb_section fb_built=”1″ _builder_version=”4.16″ custom_margin=”||50px||false” custom_margin_tablet=”” custom_margin_phone=”||0px|” custom_margin_last_edited=”on|phone” custom_padding=”0px||0||false|false” global_colors_info=”{}”][et_pb_row _builder_version=”4.16″ width=”100%” max_width=”100%” custom_margin=”|||” custom_padding=”27px|0px|27px|0px|false|false” use_custom_width=”on” width_unit=”off” custom_width_percent=”100%” global_colors_info=”{}”][et_pb_column type=”4_4″ _builder_version=”4.16″ custom_padding=”0px|||” global_colors_info=”{}” custom_padding__hover=”|||”][\/et_pb_column][\/et_pb_row][\/et_pb_section][et_pb_section fb_built=”1″ custom_padding_last_edited=”on|desktop” admin_label=”About Section” _builder_version=”4.27.4″ module_alignment=”right” custom_margin=”0px||0px||false|false” custom_padding=”0px||0px||false|false” custom_padding_tablet=”||120px|” custom_padding_phone=”” global_colors_info=”{}”][et_pb_row column_structure=”3_4,1_4″ _builder_version=”4.27.4″ custom_margin=”0px||||false|false” custom_padding=”0px||||false|false” animation_style=”slide” animation_direction=”right” animation_intensity_slide=”1%” locked=”off” global_colors_info=”{}”][et_pb_column type=”3_4″ _builder_version=”4.16″ custom_padding=”|||” global_colors_info=”{}” custom_padding__hover=”|||”][et_pb_text _builder_version=”4.27.4″ text_font=”Poppins||||||||” text_font_size=”16px” text_line_height=”2em” global_colors_info=”{}”]<\/p>\n
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In recent years, the use of big data in mobility planning<\/strong> has revolutionised the way authorities and administrations understand and manage the territory. Thanks to the integration of heterogeneous sources and advanced technologies, it is now possible to analyse complex phenomena with an unprecedented level of detail and reliability. To support this approach, data visualisation<\/strong> makes data accessible, readable and immediately interpretable even by those without technical expertise. <\/p>\n We have developed solid experience in using big data for urban and metropolitan mobility. Through a network of technical and commercial partnerships, we access continuously updated<\/strong> data sources such as: <\/p>\n This data is integrated and analysed using advanced algorithms to improve the accuracy and reliability of reconstructions.<\/strong> The aim is to provide realistic mobility analyses and identify emerging behaviours. <\/p>\n The integration of sources allows us to reconstruct Origin-Destinatio<\/strong>n matrices and describe the behaviour of users, commuters, occasional visitors and workers. We also analyse: <\/p>\n These analyses support public administrations in understanding mobility needs and defining effective operational strategies<\/strong>.<\/p>\n The processing procedures are designed to be transparent and replicable<\/strong>. Integration with territorial data allows for precise identification of: <\/p>\n The analyses thus become a solid technical basis for planning public policies<\/strong> and monitoring their performance over time.<\/p>\n To enhance the value of datasets generated by analytical processes, we develop clear and intuitive solutions<\/strong>. Our solutions include: <\/p>\n These tools facilitate the reading and interpretation of mobility phenomena even by non-technical users, improving the quality of decision-making processes.<\/p>\n Dashboards and control panels allow you to analyse:<\/p>\n These representations are designed for administrations, technicians and stakeholders <\/strong> who need to compare scenarios and assess impacts in a uniform and objective manner.<\/p>\n The synergy between big data and data visualisation<\/strong> provides a coherent and layered view of the territory. This approach: <\/p>\n Furthermore, it ensures consistency between alternative scenarios<\/strong>, making comparisons between design options clearer and more reliable.<\/p>\n The use of big data in mobility planning<\/strong>, combined with advanced visualisation tools, is now an essential standard. Our solutions integrate accurate analysis, reliable sources and readable representations to support institutions and administrations in developing more informed, sustainable and effective public policies. <\/p>\n The future of mobility is based on data: interpreting it correctly is the key to better planning.<\/p>\n [\/et_pb_text][et_pb_accordion _builder_version=”4.27.4″ _module_preset=”default” global_colors_info=”{}”][et_pb_accordion_item title=”What is Floating Car Data?” open=”on” _builder_version=”4.27.4″ _module_preset=”default” global_colors_info=”{}”]<\/p>\n This data is collected from moving vehicles (via GPS) and provides information on traffic flows, speeds and journey times in real time.<\/p>\n [\/et_pb_accordion_item][et_pb_accordion_item title=”Why is it useful to integrate multiple data sources?” _builder_version=”4.27.4″ _module_preset=”default” global_colors_info=”{}” open=”off”]<\/p>\n To increase the reliability of analyses and better describe different behaviours, from commuters to occasional users.<\/p>\n [\/et_pb_accordion_item][et_pb_accordion_item title=”What is an Origin-Destination Matrix?” _builder_version=”4.27.4″ _module_preset=”default” global_colors_info=”{}” open=”off”]<\/p>\n It is a representation of movements between geographical areas, useful for planning transport networks and analysing flows.<\/p>\n [\/et_pb_accordion_item][et_pb_accordion_item title=”What are the advantages of data visualisation?” _builder_version=”4.27.4″ _module_preset=”default” global_colors_info=”{}” open=”off”]<\/p>\n It allows complex data to be understood immediately, improving communication, comparison between scenarios and operational decisions.<\/p>\n [\/et_pb_accordion_item][et_pb_accordion_item title=”Who can benefit from these tools?” _builder_version=”4.27.4″ _module_preset=”default” global_colors_info=”{}” open=”off”]<\/p>\n Public administrations, technical consultancies, planners and stakeholders involved in decision-making processes related to urban mobility.<\/p>\n [\/et_pb_accordion_item][\/et_pb_accordion][\/et_pb_column][et_pb_column type=”1_4″ _builder_version=”4.16″ custom_padding=”|||” global_colors_info=”{}” custom_padding__hover=”|||”][et_pb_text _builder_version=”4.27.4″ text_font=”Poppins||||||||” text_font_size=”13px” text_line_height=”1.1em” custom_margin=”10px||||false|false” global_module=”293″ saved_tabs=”all” locked=”off” global_colors_info=”{}”]<\/p>\n PIANIFICAZIONE DELLA MOBILIT\u00c0<\/strong><\/span><\/a><\/p>\n PROGETTAZIONE URBANA<\/b><\/span><\/a><\/p>\n INDAGINI E RILIEVI DEI FLUSSI DI MOBILIT\u00c0<\/strong><\/span><\/a><\/p>\n PROCESSI PARTECIPATIVI<\/strong><\/span><\/a><\/p>\nBig Data applied to mobility: sources, methods and objectives<\/h3>\n
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From O\/D matrices to systematic behaviours<\/h3>\n
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Transparency, replicability and decision support<\/h3>\n
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Data Visualisation: making data visible and readable<\/h3>\n
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Comprehensive analyses for planning and design<\/h3>\n
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Integration between analysis and visualisation: a single ecosystem<\/h3>\n
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Conclusion<\/h3>\n