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Abstract
With the extensive use of digital signage, precise site selection is an urgent issue for digital signage enterprises and management agencies. This research aims to provide an accurate digital signage site-selection model that integrates the spatial characteristics of geographical location and multisource factor data and combines empirical location models with machine learning methods to recommend locations for digital signage. The outdoor commercial digital signage within the Sixth Ring Road area in Beijing was selected as an example and was combined with population census, average house prices, social network check-in data, the centrality of traffic networks, and point of interest (POI) facilities data as research data. The data were divided into 100–1000 m grids for digital signage site-selection modelling. The empirical approach of the improved Huff model was used to calculate the spatial accessibility of digital signage, and machine learning approaches such as back propagation neural network (BP neural networks) were used to calculate the potential location of digital signage. The site of digital signage to be deployed was obtained by overlay analysis. The result shows that the proposed method has a higher true positive rate and a lower false positive rate than the other three site selection models, which indicates that this method has higher accuracy for site selection. The site results show that areas suitable for digital signage are mainly distributed in Sanlitun, Wangfujing, Financial Street, Beijing West Railway Station, and along the main road network within the Sixth Ring Road. The research provides a reference for integrating geographical features and content data into the site-selection algorithm. It can effectively improve the accuracy and scientific nature of digital signage layouts and the efficiency of digital signage to a certain extent.
Highlights
Digital signage is a multimedia audio–visual system that releases business, financial, and entertainment information through terminal display devices in public places [1,2]
To verify the accuracy of the abovementioned digital signage site‐selection method, we compare our method with the BP neural network model in the machine learning method and the Huff and multiplicative competitive interaction (MCI) empirical model of commercial geography
A lower false positive rate and higher true positive rate, 1t6hoaft2i1s, the closer the Receiver operating characteristic (ROC) curve is to the upper left, indicate the model has higher accuracy and better site iserlelcattiiovneleyffhecigt.h and its false positive rate is relatively low—the curve is closest to the top left, which showTs htheelolcoactaitoionnreesfufeltcst ooff etahcish emxpodereilmaernetshisorwenlatiinvFeliygugroeo1d0,.fTohlleowreesdulbtyofththeeBBPPnneeuurraallnneettwwoorrkk mmooddeell. iBsosthhotwhen HinuFfifgmuroed1e0laa.nUdstihnegM10C0–I 1m00o0deml amreodperollbinagbiflaisctiocrsmaosdienlps,uatnodf tthheeBloPcnateiuornael fnfetcwtsoorfk tmheotdweol, aarsetshiemmilaord, ethlleinregbsycvaleeriifnycinregatshees,atchceurRaOcyCacnudrvreeligarbaidlituyaollfythapisperxopaecrhimesetnhte
Summary
Digital signage is a multimedia audio–visual system that releases business, financial, and entertainment information through terminal display devices in public places [1,2]. The first is the study of consumers’ behaviour by using digital signage. Digital signage can promote a retail atmosphere and stimulate consumption behaviour [10,11,12,13,14]. The second focus is on the system development for digital signage management and content distribution. Emerging technologies represented by big data technology have promoted the development of intelligent platforms for digital signage terminal management, automatic scheduling, and content distribution [17,18,19,20]. Empirical digital signage site selection and advertisement placement are all performed manually, and there is a lack of data and method standards, which make it difficult to meet the needs of advertisers and media dealers. Precise location models should be introduced to digital signage for standardized management, which is an urgent problem for digital signage enterprises
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