Found 15 repositories(showing 15)
MobilityData
Documentation for the General Bikeshare Feed Specification, a standardized data feed for shared mobility system availability. Maintained by MobilityData
openmobilityfoundation
A data specification to enable right-of-way regulation, digital policy, geofencing, and two-way communication between mobility companies and public agencies worldwide for any regulated, shared vehicle.
CDSM-WG
City Data Specification for Mobility
VDVde
Data definitions for the VDV Internet of Mobility specifications - Topics & Payloads for MQTT
UnionInternationalCheminsdeFer
api specification for the exchange of real time mobility data
SFOE
Swiss Shared Mobility Data Specification (SSMDS)
cityofaustin
[Deprecated] A Python utility to interact data endpoints compliant with the Mobility Data Specification, as designed by the Open Mobility Foundation
PoojaPatel35
Project Proposal : Computer simulation has been used for years now in medical industries including the study of infectious disease. As the virus is spreading easily to the people who are infected but not showing the symptoms, we are in the global pandemic situation. And so all the countries are reporting the increase number of COVID -infected people. And as all the scientists are working to prevent the spreading of this virus. I am building a simple demonstration project to simulate the corona virus spread on different scenario using various parameters and in totally varying environment. It will help to examine and Strengthen existing plans. Some of the articles indicate that governments are relying upon the mathematical model to help guide the decision to overcome the decision. A model can forecast the future impacts according to the past records. A Simulation can help with that and if it can be made with some specification like sex, age, health status, employment It can be easy for the government or some business leaders to take decision in advance to benefit the society. Simulator will show some numbers of infecting people day to day on various situation, like what will 100% lockdown will impact of spreading the virus or what a self-isolation can help with. What is the capacity of the virus to spread and people can be Re-infected or not and if then at what range? I can also prepare simple simulation which shows the normal thing going around in normal days and compare both the situations. As thigs are little in control, I can also show simulation where people are staying home and only going out when needed and how mobility is reduced. Even after the lockdown the rate of infected people will be increasing and what it the rate of the infected people and when it is starting to decrease. As reality is more complex, lets give some aspects to the needy to make a great decision with the simulation which may inject some randomness but give forecast. We need some different intensity data to evaluate the system outcome
markohelbiz
No description available
No description available
mobilityDCAT-AP
A metadata specification for mobility data platforms
openmobilityfoundation
API specification that facilitates in-field mobility data collection. [DRAFT]
signDomeX
Documentation for the General Bikeshare Feed Specification, a standardized data feed for shared mobility system availability. Maintained …
The main objectives of this project are (1) propose a characterization of mobile and immobile population, where mobility will be defined by the number of trips that a person has made, and (2) identify the specifications of mobility and predict the mobility of citizens based on the specifications. Unsupervised and Supervised learning methods are applied for Characterization and Prediction Respectively. The specific focus of the paper will be on the effect of car ownership on immobile population. In order to achieve this objective the data describe the trips made by members of Grenoble households (Cerema (2013) is used.
Saquibtechlotraining
This project analyzes data from the 91wheels website (as of Nov 10, 2023) on electric scooters in India 🛴, reflecting the rising popularity of EVs ⚡. With 85 companies offering 288 models across 436 variants, it explores the evolving landscape 🌏, consumer preferences 💡, and scooter specifications 📊 amidst the transition to electric mobility 🔋.
All 15 repositories loaded