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Designing an Intelligent Advertising Business Model in Seoul's Metro Network (서울지하철의 지능형 광고 비즈니스모델 설계)

  • Musyoka, Kavoya Job;Lim, Gyoo Gun
    • Journal of Intelligence and Information Systems
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    • v.23 no.4
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    • pp.1-31
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    • 2017
  • Modern businesses are adopting new technologies to serve their markets better as well as to improve efficiency and productivity. The advertising industry has continuously experienced disruptions from the traditional channels (radio, television and print media) to new complex ones including internet, social media and mobile-based advertising. This case study focuses on proposing intelligent advertising business model in Seoul's metro network. Seoul has one of the world's busiest metro network and transports a huge number of travelers on a daily basis. The high number of travelers coupled with a well-planned metro network creates a platform where marketers can initiate engagement and interact with both customers and potential customers. In the current advertising model, advertising is on illuminated and framed posters in the stations and in-car, non-illuminated posters, and digital screens that show scheduled arrivals and departures of metros. Some stations have digital screens that show adverts but they do not have location capability. Most of the current advertising media have one key limitation: space. For posters whether illuminated or not, one space can host only one advert at a time. Empirical literatures show that there is room for improving this advertising model and eliminate the space limitation by replacing the poster adverts with digital advertising platform. This new model will not only be digital, but will also provide intelligent advertising platform that is driven by data. The digital platform will incorporate location sensing, e-commerce, and mobile platform to create new value to all stakeholders. Travel cards used in the metro will be registered and the card scanners will have a capability to capture traveler's data when travelers tap their cards. This data once analyzed will make it possible to identify different customer groups. Advertisers and marketers will then be able to target specific customer groups, customize adverts based on the targeted consumer group, and offer a wide variety of advertising formats. Format includes video, cinemagraphs, moving pictures, and animation. Different advert formats create different emotions in the customer's mind and the goal should be to use format or combination of formats that arouse the expected emotion and lead to an engagement. Combination of different formats will be more effective and this can only work in a digital platform. Adverts will be location based, ensuring that adverts will show more frequently when the metro is near the premises of an advertiser. The advertising platform will automatically detect the next station and screens inside the metro will prioritize adverts in the station where the metro will be stopping. In the mobile platform, customers who opt to receive notifications will receive them when they approach the business premises of advertiser. The mobile platform will have indoor navigation for the underground shopping malls that will allow customers to search for facilities within the mall, products they may want to buy as well as deals going on in the underground mall. To create an end-to-end solution, the mobile solution will have a capability to allow customers purchase products through their phones, get coupons for deals, and review products and shops where they have bought a product. The indoor navigation will host intelligent mobile-based advertisement and a recommendation system. The indoor navigation will have adverts such that when a customer is searching for information, the recommendation system shows adverts that are near the place traveler is searching or in the direction that the traveler is moving. These adverts will be linked to the e-commerce platform such that if a customer clicks on an advert, it leads them to the product description page. The whole system will have multi-language as well as text-to-speech capability such that both locals and tourists have no language barrier. The implications of implementing this model are varied including support for small and medium businesses operating in the underground malls, improved customer experience, new job opportunities, additional revenue to business model operator, and flexibility in advertising. The new value created will benefit all the stakeholders.

A Numerical Study on the Characteristics of Flows and Fine Particulate Matter (PM2.5) Distributions in an Urban Area Using a Multi-scale Model: Part II - Effects of Road Emission (다중규모 모델을 이용한 도시 지역 흐름과 초미세먼지(PM2.5) 분포 특성 연구: Part II - 도로 배출 영향)

  • Park, Soo-Jin;Choi, Wonsik;Kim, Jae-Jin
    • Korean Journal of Remote Sensing
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    • v.36 no.6_3
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    • pp.1653-1667
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    • 2020
  • In this study, we coupled a computation fluid dynamics (CFD) model to the local data assimilation and prediction system (LDAPS), a current operational numerical weather prediction model of the Korea Meteorological Administration. We investigated the characteristics of fine particulate matter (PM2.5) distributions in a building-congested district. To analyze the effects of road emission on the PM2.5 concentrations, we calculated road emissions based on the monthly, daily, and hourly emission factors and the total amount of PM2.5 emissions established from the Clean Air Policy Support System (CAPSS) of the Ministry of Environment. We validated the simulated PM2.5 concentrations against those measured at the PKNU-AQ Sensor stations. In the cases of no road emission, the LDAPS-CFD model underestimated the PM2.5 concentrations measured at the PKNU-AQ Sensor stations. The LDAPS-CFD model improved the PM2.5 concentration predictions by considering road emission. At 07 and 19 LST on 22 June 2020, the southerly wind was dominant at the target area. The PM2.5 distribution at 07 LST were similar to that at 19 LST. The simulated PM2.5 concentrations were significantly affected by the road emissions at the roadside but not significantly at the building roof. In the road-emission case, the PM2.5 concentration was high at the north (wind speeds were weak) and west roads (a long street canyon). The PM2.5 concentration was low in the east road where the building density was relatively low.