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Purpose A fundamental concept of the smart city is to get the right information at the right place to make city-related decisions easier and quicker. The main goal of supply chain management (SCM) systems is to enhance the supply chain process for delivering the identified products to customers correctly in distributed organizations. In addition, new IT infrastructure such as cloud-based systems and internet of things (IoT) have changed many organizations and firms. Hence, this study aims to assess the factors that contribute to the success of SCM systems. Design/methodology/approach In this paper, the usage of urban knowledge, urban intelligent transportation systems and IT infrastructure was considered as a key factor for the success of SCM systems. For assessing the features of the model, a comprehensive questionnaire was designed. The survey questionnaires were sent to critical informers who are practical heads associated with SCM and urbanism. Of these, 315 usable responses were received, resulting in a response rate of 82.03%. The data were examined using Smart-PLS version 3.2 and IBM SPSS version 25. Findings The obtained results showed the high strength of the proposed model. This study found that the impact of urban ITS (safety, accessibility, information management and flexibility) is important to the success of supply chain management systems. Another important finding is that the cloud-based system (cloud security, resource virtualization, on-demand self-service and scalability) has a very important role in the success of supply chain management systems. The finding showed that the effect of IoT service variable (commercialization, mobility features, infrastructure capabilities and security and privacy) on the success of supply chain management systems is significant and positive. The findings also showed that urban knowledge (usage skills, awareness, experience and knowledge sharing) is viewed as a significant factor in the success of supply chain management systems. Research limitations/implications The inductive nature of research methodology has introduced limitations on the generalizability of results. Therefore, it is recommended to examine the validity of this research model in other supply chains. Practical implications The statistical results support the crucial role of urban knowledge, urban intelligent transportation systems, IoT services and cloud-based systems. Therefore, aspects relating to these factors must be the focus of attention of any distributed organization in their endeavor to develop supply chain management systems. Implementing cloud based IoT through accurate and timely availability of information, can predict forecasting and planning processes, resources, logistics and support, service management and spare parts and many sub-processes in the supply chain. These technologies allow organizations to invest in manufacturing and operating processes rather than paying for the software section, which will generate more cash flow. Originality/value One of the most crucial and fundamental parts of an organization’s management is the supply chain management. The department is responsible for coordinating all units from the initial stages, such as supplying materials to the final stages, such as delivery and after-sales service. Comprehensive and credible information platforms are essential for managing a supply chain. Therefore, it is important to use integrated information systems such as IoT, cloud computing, intelligent transportation systems and more in this part of the organization management. Covering this information in a timely and accurate manner will facilitate the process and make the process more transparent. For this purpose, a model is needed to determine the relationship between technologies and supply chain management, which this study has provided a comprehensive model.

In order to implement a computer vision based reading recognition system for pointer gauges, we propose an algorithm to locate the pointer by searching for the minimal bounding rectangle (MBR) of the pointer region. Having determined the center of dial region and the centroids of scale marks, we build up a reference system for reading recognition with the dial region center and the scale mark centroids. To identify the indicating value of a gauge image, we first detect the pointer region based on frame difference, and determine the MBR of the pointer using the longest edge of its convex hull. We then take the centroid of the MBR enclosing the pointer region as the centroid of the pointer. We next take the connection between the pointer centroid to the dial center as the pointer, and calculate the indicating value corresponding to the pointer based on the angle method. Experimental results reveal the effectiveness of the pointer location algorithm in computer vision based reading recognition for pointer gauges.

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Castanea henryi , with edible nuts and timber value, is a key tree species playing essential roles in China's subtropical forest ecosystems. However, natural and human perturbations have nearly depleted its wild populations. The study identified the dominant environmental variables enabling and limiting its distribution and predicted its suitable habitats and distribution. The 212 occurrence records covering the whole distribution range of C. henryi in China and nine main bioclimatic variables were selected for detailed analysis. We applied the maximum entropy model (MaxEnt) and QGIS to predict potentially suitable habitats under the current and four future climate‐change scenarios. The limiting factors for distribution were accessed by Jackknife, percent contribution, and permutation importance. We found that the current distribution areas were concentrated in the typical subtropical zone, mainly Central and South China provinces. The modeling results indicated temperature as the critical determinant of distribution patterns, including mean temperature of the coldest quarter, isothermality, and mean diurnal range. Winter low temperature imposed an effective constraint on its spread. Moisture served as a secondary factor in species distribution, involving precipitation seasonality and annual precipitation. Under future climate‐change scenarios, excellent habitats would expand and shift northwards, whereas range contraction would occur on the southern edge. Extreme climate change could bring notable range shrinkage. This study provided a basis for protecting the species' germplasm resources. The findings could guide the management, cultivation, and conservation of C. henryi , assisted by a proposed three‐domain operation framework: preservation areas, loss areas, and new areas, each to be implemented using tailor‐made strategies.