Smart tourism village, opportunity, and challenge in the disruptive era

Rudwiarti, Lucia Asdra; Pudianti, Anna; Emanuel, Andi Wahju Rahardjo; Vitasurya, Vincentia Reni; Purwanto, Hadi

doi:10.1088/1755-1315/780/1/012018

Cited by 12 publications

(7 citation statements)

References 3 publications

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“…In the process of operation, different from the traditional fixed tourism mode, tourists are regarded as the core of the entire tourism development, and the user actively integrates entertainment, shopping, play, travel, accommodation and meals, and other aspects for users. It fully integrates informatization and tourism to achieve the goal of personalized service [11][12][13][14][15].…”

Section: Introductionmentioning

confidence: 99%

Optimization of Rural Smart Tourism Service Model with Internet of Things

2022

Security and Communication Networks

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Rural smart tourism is a new tourism form supported by information technology, especially the Internet of Things technology. Smart tourism not only makes it easier for tourists to get diverse tourism information, but it also helps attractive sites improve their service capabilities. The optimization of the rural smart tourist service model, which is explored in this work, includes personalized recommendations of scenic sites. The main research contents of the paper are as follows: (1) A new algorithm for recommending tourism destinations with domain adaptability has been suggested. In the field of personalized recommendation of tourist attractions, most of the target domain data are unlabeled, and the model cannot be trained. When it comes to training, however, there exist source domain data sets that are completely labeled and can be used as a supplement to the target domain training data sets. (2) A personalized recommendation algorithm for tourist attractions with deep migration has been studied. Owing to the distribution difference between target data and source data, an adaptive layer is added to the convolutional neural network. The domain loss is then minimized to achieve deep feature transfer, and the model can then be trained to find scenic areas of interest to the user. Finally, the recommendation for tourist destinations with deep migration is done by examining the relationship between the target user and other users.

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Section: Introductionmentioning

confidence: 99%

Optimization of Rural Smart Tourism Service Model with Internet of Things

2022

Security and Communication Networks

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“…e demand for forest smart tourism can be divided into four stages: Travel Dream ⟶ Travel Plan ⟶ Booking and Payment ⟶ Comment/Share, forming the DPB-S (dream, plan, and book-share) cycle of smart tourism demand [28]. Focusing on the demand of smart tourism, the model is constructed from two dimensions: vertical service process and horizontal service interaction.…”

Section: Establishment Of the Smart Tourism Service Modelmentioning

confidence: 99%

Development Potential of the Internet of Things-Based Forest Recreation under the Background of Informatization

Feng

Zhang

Liu

2022

Mobile Information Systems

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There are few studies on forest smart tourism currently, and most smart tourist service models are only studied and analyzed theoretically. Based on this, the Internet of Things (IoT), mobile communications technology, and smart tourism related ideas are discussed in depth in this study, followed by the construction of a forest smart tourist service model. The forest smart tourism evolutionary game model is then built based on the benefit relationships of various tourist sectors. Finally, the effect of the forest smart tourist service model and the forest smart tourism service evolutionary game model is evaluated using simulation experiments. The findings show that (a) daily passenger flow data from scenic spots in June was scattered, but the overall estimate gives that the daily passenger flow was more than 800; (b) daily passenger flow data from scenic spots in December was scattered, but overall estimate shows that the daily passenger flow was less than 300; and (c) the average profit value of the game model was 3.5, 3, and 6, respectively, under various circumstances. To summarize, the model provided in this paper is reliable and appropriate for optimizing forest smart tourist services. Through the constructed model, this work seeks to give theoretical reference for further boosting the development potential of forest recreation.

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“…Prasarana wisata adalah sumber daya alam dan manusia yang dibutuhkan oleh wisatawan dalam perjalanannya dari dan menuju objek wisata (Sugandini et al, 2018) (Rudwiarti et al, 2021). Prasarana wisata meliputi aksesibilitas, utilitas, dan jaringan jalan atau kondisi jalan objek wisata berada.…”

Section: Prasarana Wisataunclassified

Strategi Rintisan Pariwisata Terintegrasi dan Berkelanjutan di Kota Semarang

Trimartuti

Prajanti

Rahayuningsih

et al. 2022

RIPTEK

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Gunungpati District has an ex-JSDF land area of 73.2 ha consisting of 67 parcels of land spread across 12 Sub-Districts. The ex-JSDF land area was originally a poverty alleviation program and critical land conservation in the City of Semarang in collaboration with the JSDF (Japanese Social Development Fund), Worldbank and the City Government of Semarang. The development of several ex-JSDF land locations has developed into agro-tourism areas such as those managed by the Agriculture Service in Cepoko Village. However, several other locations managed by farmer groups were abandoned and then experienced land conversion. So that the potential of the ex-JSDF in the region was identified to obtain a pilot strategy for sustainable tourism in the city of Semarang. The research was carried out by identifying tourist attractions and tourism development factors so that directions for developing integrated and sustainable tourism areas in Gunungpati District could be obtained. the results of the analysis of the suitability of cultivated land in the former JSDF land locations spread across 12 sub-districts, 11 of which have an S1 suitability class, namely its use is very suitable for cultivating fruit crops. Meanwhile, one other location, namely Sumurrejo Village, has a Masters degree of suitability (quite appropriate). In general, the limiting factors in the heavy research sites were soil texture and fertility which were in class S3. Another mild limiting factor is temperature and groundwater productivity which are in class S2. Sustainability analysis found that the level of sustainability of fruit cultivation on ex-JSDF land in the Gunungpati District area was in a less sustainable status, the resulting index value only reached 58.94. Integrated tourism development area in Kec. Gunungpati with the main tourism zones covering, 1) Agroeduwisata Kandri Tourism Village, 2) Kreo Cave & Jatibarang Reservoir, 3) Kandri Boat Tourism, 4) Ngrembel Asri, and 5) Firdaus Fatimah Zahra.

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Smart tourism village, opportunity, and challenge in the disruptive era

Cited by 12 publications

References 3 publications

Optimization of Rural Smart Tourism Service Model with Internet of Things

Optimization of Rural Smart Tourism Service Model with Internet of Things

Development Potential of the Internet of Things-Based Forest Recreation under the Background of Informatization

Strategi Rintisan Pariwisata Terintegrasi dan Berkelanjutan di Kota Semarang

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