TechOffers

SDE001  |  Social Networking Platform for Travel

This technology is a new generation of social networking platform based on travel experience. Travellers around the world are allowed to connect with their trips remotely from their travel destinations. Anyone can create a trip and invite others to join, or simply join trips created by others. Users can be flexible with their dates of check-in and check-out as long as they are within a fortnight.  

Exhibitor : Anezt Group

SDE048  |  Creating Cyber-Physical Social Networks

This technology connects people with shared interests. Users’ interest derives from a user’s current location in the physical world as well their browsing activity on the Web (virtual world) and are typically short lived. As a Cyber-Physical Social network, our platform enables fine grained context specific services while enabling users to discover one another. 

Exhibitor : NUS Enterprise

SDE050  |  Real-time Collaboration on a Shared Map with Multiple Displays

This technology is a multi-display system that supports real-time collocated collaboration on a shared map. It provides rich user interactions by introducing activity awareness and view sharing capability to enable seamless information sharing and integration in map-based applications. It can be used in conjunction with several tablet devices, laptops, and shared large displays.

Exhibitor : NUS Enterprise

SDE073  |  Technology Management and Validation Hub

This is a Technology Hub to accelerate validation, simplify portfolio management and facilitate network engagement for tech owners, entrepreneurs, professionals, business partners, investors and industry contacts. Our solution offers a new method and set of tools which gives you all the visibility and control you need to easily manage and track your portfolio within team while engaging with all third-parties.

Exhibitor : Sehir TTO

SDE083  |  Bus Analytics Using Twitter

In a rapidly growing city population, a commuter friendly public transport system is essential in coping with the increasing demands of a thriving city. We propose a crowdsensing framework to gather and analyse real-time commuter feedback from Twitter. We perform text mining tasks to identify feedback comments containing bus-related micro-events; extracting entities; and, predicting event and sentiment labels. The experiments show that our domain-sensitive text analysis models are effective. We further solicit structured feedback tweets from commuters. This technology is useful in gathering feedback for all service-oriented systems. 

Exhibitor : SMU Living Analytics Research Centre

SDE084  |  Context-Aware Mobile Crowdsourcing and Logistics

By effectively utilising smartphones to reach out and engage a large population of mobile users, mobile crowdsourcing can become a game-changer for many urban operations, such as last-mile logistics and municipal monitoring. To overcome the uncertainties and risks associated with an opportunistic model of traditional crowdsourcing, we have developed a centrally-coordinated task assignment/recommendation technology. This technology matches workers to tasks that lie along their predicted movement paths and incorporates mechanisms to elicit higher levels of task acceptance by users.  Our technologies have been embedded and demonstrated at our university campus, via a real world mobile crowd-tasking platform.

Exhibitor : SMU Living Analytics Research Centre

SDE085  |  Facebook Data Analytics: Finding the Strategic Business Location

Choosing an optimal physical location to set up a new business is a crucial decision that affects the success of a potential business. Business owners have to consider factors such as potential customers, competitors, and complementary businesses. In social media, there exists plenty of online user-generated data through which business owners learn about their potential customers, business competitors, and popular locations. This project uses Facebook data to provide insights to find ideal locations for business owners so as to increase their success.

Exhibitor : SMU Living Analytics Research Centre

USS011  |  Incentive-based Crowd Management

The crowd management technology aims to mitigate congestion in transportation modes, especially at the end of a large-scale event, by changing people’s behaviour, while enhancing their experience. Optimised recommendation provided through mobile app consists of an assortment of options which are combinations of transportation mode, estimated congestion levels and incentives such as coupons. Our optimisation technology considers user profit and social welfare at the same time and provides well-designed options to help a user choose appropriate egress time which helps to disperse congestion as well as allows the user to enjoy incentives.

Exhibitor : Fujitsu-SMU Urban Computing & Engineering Corp Lab