In a large-scale national forest recreation park, it is difficult for park managers to maintain facilities and provide timely or emergency services to visitors in need (e.g., elderly adults, children, or lost visitors without communication devices). To implement smart tourism services, park managers have introduced the Internet of things (IoT) to their parks, which has enabled the provision of diversified intelligent information services. However, most of the previous studies focused on 2D deployment of the IoT system to cover all targets, ignoring actual 3D topographic differences; their objectives rarely included the effectiveness of services generated from introducing the IoT; they assumed targets to be equally crucial, regardless of differences in tourism attractiveness (e.g., tourist attractions, view trails, and recreation facilities). Therefore, this study investigates 3D deployment of an IoT system to cover targets with different scores based on tourism attractiveness in a forest recreation park with optimal management service benefits, represented as a weighted sum of service quality index (SQI) and managerial setting attributes index (MSAI), so that the system collects the data from visitors equipped with wearable devices, and applies it to tasks such as physiological detection and positioning. This problem belongs to deployment and coverage problems, which have been shown to be NP-hard, and thus is also NP-hard. Therefore, this study further solves this problem by improved simulated annealing (ISA), including three neighborhood searching operators and the dynamic probability adjustment scheme. Experimental results under various parameter settings indicate that ISA has an excellent optimization ability.
