Intelligent Crowd and Human Intelligence

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SENSE SMART

Sensors embedded solutions with inbuilt characteristic of artificial intelligence’s to solve the problem of distributing crowds more evenly (especially during peak periods) along trains and platform.

  • Acquisition of the information’s in real time.
  • Tracking & Processing of the information’s in real time.

End-to-End incentivized and trust-enabled participatory sensing framework optimizing sensor network performance, based on integrated and interactive visualization platform

The app’s role is to find the least crowded train carriage for users and to help them, in the case of connections, to reduce their walking itinerary on platform & best use of foot over bridge connecting the platform on rail network.

Assign a carriage to each user: before arriving at a station where a user is standing and waiting for a train, the user is informed of the carriage with the least travelers. Thus, the user can walk to the area where he will get into the assigned train coach. Moreover, on a stormy or rainy day, a user can be notified about when he/she should leave the office or home to synchronize both train and passenger arrival at the platform.

Improve comfort outside the train to enhance the travel experience (fluidity of platform traffic): after receiving the assigned coach number, the passenger swiftly positions himself in front of the train coach according to the station’s guidance marks. For travelers with connecting journeys, choosing the wrong train coach can lead to congestion on platforms.

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Imagining Passengers: A got into the carriage located at the head end of a train and Passenger B got into one located at the opposite end. However, what if the nearest connection itinerary was from the tail end of the train for Passenger A and the opposite end for Passenger B? Those two passengers would probably cross on the platform, which could cause congestion.

Advising passengers / travelers: Data gathered from rail network traffic, it can be possible to advise people taking a train in a specific time range.

People interact live: Users can report a problem occurring on either the train or the whole rail network.

The system assumes that sensors along platforms & trains count & estimate the crowd density and display this information to commuters display system.

  • Monitor crowd density of each carriage and display the crowd distribution of the train together with the “next train” timing at the passenger display system.
  • This allows travelers to know which carriages are less crowded and be able to adjust appropriately by waiting at the door of the less crowded carriage before the train arrives
  • Assign a carriage to each user: before arriving at a station where a user is standing and waiting for a train, the user is informed of the carriage with the least travelers.
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When Commuters tap in using application, it recommends a carriage based on crowd density around platform exits at the destination and carriage density.

Ease to Use

  • Plug-and-Play sensor node architecture and network for reliable data collection and dissemination.
  • Turning travelers & citizens into sensors? Anyone can download a civic app to their smart phone and use it to find out what’s happening at boarding point of stations & MRTS they happen to be passing by.
  • But the app also lets travelers/citizens upload information of their own, geo code it and send it to the city, so that others can share the information.
  • Web Interface: The server is responsible for receiving, storing, fetching, and visualizing the data it receives from the city eco system.
  • Measurement System: Embedded devices for our needs to measure some quantity (distance sensors for volume, force sensors for weight, etc.) are beyond the price and performance range of the application
  • End-to-End incentivized and trust-enabled participatory sensing framework optimizing sensor network performance design, based on integrated and interactive visualization platform.
  • Look for less expensive options. Can���t afford to install a network of sensors? Consider putting sensors with GPS trackers on city-owned vehicles, turning them into mobile sensing devices for traffic and environmental monitoring, to name just a couple of possibilities. Scour through existing data to identify potential hot spots for where to selectively place sensors, reducing the number of devices needed to monitor traffic, transit or water lines, for example.
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