ObjectiveThe purpose of the current studies was to use direct observation and surveys to assess behavioral risk on a college campus during the COVID-19 pandemic.MethodsStudy 1 used direct observation to monitor safe and at-risk mask-wearing behavior across multiple campus locations and whether mask-wearing differed when individuals were alone or in groups. Study 2 surveyed college students through a click-based campus map survey to identify high- and low-mask-wearing locations on campus and create data heat maps indicating at-risk behaviors. Direct observation analyses were then used to verify the identified locations.ResultsStudy 1 revealed that mask-wearing was likely during a mask-wearing policy implemented across the college campus. However, mask-wearing was less likely when people were in groups than alone. Study 2 showed that survey responses and the heat map analysis identified spatially distinct locations of perceived high and low mask-wearing. These data were validated through direct observation, verifying high and low mask-wearing at the identified locations.ConclusionsSurvey heat maps paired with direct observation can help identify specific locations where safe and at-risk behaviors are most likely to occur. By identifying special patterns of risk, this comprehensive approach offers actionable information to guide interventions, policy enforcement, and resource allocation during health epidemics.

Loneliness and social (dis)connectedness are significant public health concerns, particularly among university students. Despite calls to reconceptualise loneliness as a systemic issue, interventions typically target individual students. This series of studies used a sequential mixed-methods and participatory action approach to explore students' social experiences and co-design a digital health solution. Focus groups (Study One) and a survey (Study Two) revealed that students see universities as partly responsible for their social connectedness, with perceptions of campus space being key. These insights informed the co-design of MAPP (Study Three), a preventative, system-focused digital solution. MAPP is an interactive campus map that visualises the university's living social network. It increases the visibility and accessibility of the university community to foster belonging, scaffold social engagement, and support institutional inclusivity. By shifting focus from the lonely student to the university as a social system, MAPP offers a novel, holistic response to student loneliness.

This study presents the development and evaluation of a Quick Response (QR) code-integrated, web-based, and GIS-supported interactive learning model designed to enhance field-based plant learning in landscape architecture education. Conducted on the Görükle Campus of Bursa Uludağ University (BUU), the research systematically inventoried 6869 individual woody plants belonging to 172 taxa, georeferenced them using GPS, and visualized the data on an interactive campus map. Unique QR codes were generated for each taxon, providing instant access to plant profiles via a web platform and the Landscape Plants mobile application. The pedagogical effectiveness of the system was evaluated through a survey administered to 158 students, yielding a high internal reliability (Cronbach’s Alpha = 0.969). The findings indicated a high level of student satisfaction and a strong positive correlation between web-based and QR code applications (r = 0.941, p ≤ 0.001). This research represents the most comprehensive campus-scale digital plant learning system in Turkey, in terms of both species diversity and individual count. It provides a scalable and sustainable smart campus model which is applicable to nature-based disciplines worldwide.

This paper presents a markerless augmented reality (AR) navigation system for guiding users across a university campus, independent of internet or wireless connectivity, integrating machine learning (ML) and deep learning techniques. The system employs computer vision to detect campus signage “Meeting Point” and “Directory”, and classifies them through a binary classifier (BC) and convolutional neural networks (CNNs). The BC distinguishes between the two types of signs using RGB values with algorithms such as Perceptron, Bayesian classification, and k-Nearest Neighbors (KNN), while the CNN identifies the specific sign ID to link it to a campus location. Navigation routes are generated with the Floyd–Warshall algorithm, which computes the shortest path between nodes on a digital campus map. Directional arrows are then overlaid in AR on the user’s device via ARCore, updated every 200 milliseconds using sensor data and direction vectors. The prototype, developed in Android Studio, achieved over 99.5% accuracy with CNNs and 100% accuracy with the BC, even when signs were worn or partially occluded. A usability study with 27 participants showed that 85.2% successfully reached their destinations, with more than half rating the system as easy or very easy to use. Users also expressed strong interest in extending the application to other environments, such as shopping malls or airports. Overall, the solution is lightweight, scalable, and sustainable, requiring no additional infrastructure beyond existing campus signage.

The increasing size and complexity of modern campuses has created challenges in ensuring safety, security, and seamless navigation for students and visitors. Traditional manual surveillance methods and static campus maps are inadequate in providing real-time monitoring and dynamic guidance. Human-dependent monitoring is error-prone and inefficient, while students and visitors often face difficulties in locating classrooms, administrative offices, or other facilities. Moreover, issues such as inconsistent attendance tracking, class bunking, and unidentified anomalies further highlight the limitations of current systems. To address these challenges, this project proposes a software-only, machine learning–based Smart Campus Surveillance and Guidance System that leverages existing CCTV infrastructure. The system integrates face recognition for automated attendance tracking, anomaly detection for suspicious activities, and an indoor navigation module for real-time campus guidance. The solution operates without the need for additional IoT or blockchain devices, making it lightweight, cost-efficient, and scalable. The architecture comprises multiple software modules including preprocessing, face recognition, activity detection, and navigation built on graph-based pathfinding algorithms. Backend APIs and a database store all student, attendance, and anomaly data, while a user-friendly frontend provides real-time alerts and navigation. By combining deep learning models such as YOLO, FaceNet, and LSTMs with pathfinding algorithms like Dijkstra and A*, the system ensures intelligent monitoring, early anomaly detection, and smooth user navigation. This system has the potential to revolutionize campus security and student management by automating critical tasks, reducing manual errors, and improving campus safety standards. Beyond surveillance, it also enhances user experience by providing personalized route guidance and timely notifications. With privacy safeguards, scalability features, and modular deployment, this project lays a strong foundation for the adoption of AI-driven smart campuses in the future.

Abstract Campus navigation often produce challenges for students, staff, and visitors, specifically in large complex. This research presents an intelligent navigation assistant that combines automatic speech recognition (ASR), Natural Language Processing (NLP), and the A* pathfinding algorithm to tackle these issues through voice interaction. Users can naturally voice their destination queries, which the system converts into text using speech recognition techniques. Then, NLP processes the text to identify intent and relevant entities, which improves the understanding of user commands. The A* algorithm calculates the shortest path on a digital campus map and ensures effective route planning. Experimental evaluation shows high accuracy in speech-to-text conversion, effective command interpretation using NLP, and better navigation efficiency than traditional systems. This intelligent assistant improves user accessibility and convenience by providing a practical solution for hands-free campus navigation. Future work will focus on improving noise resistance, expanding language support, and integrating real-time location updates. Key Words: Intelligent Campus Navigation, Speech Recognition, Natural Language Processing (NLP), A* Pathfinding Algorithm.

The campus area is gradually expanding with the increasing number of university students. Consequently, it is difficult for freshmen or visiting staff to find a specific building at the campus. The study aimed to Develop a Campus Web GIS Navigation System for the study area using Geospatial technology. The general procedures to create a web map navigation application are Geo-referencing Images, digitization, Road Network Analysis, Overlay Analysis, and finally, a Web GIS Based Campus Navigation System has been developed. The main activity of the system application is the map activity. It displays the campus map of the Wa chemo University. The user can zoom and scroll this map to get to his/her desired places. The building map is the basic layer of this screen. The end user can access it by using this link: https://wcu- webmap.github.io/Web-Map-of-WCU/

This article details the ethical challenges we encountered while designing maps for The Harm Mapping Project. Led by Dana Cuomo, Susan Hannan, and three undergraduate student research assistants (Madison Dennehy, Meredith Forman, and Abigail Zea), The Harm Mapping Project examines the geography of gender-based violence occurring at Lafayette College, a small (approx. 2,700 undergraduate students) residential liberal arts college in Easton, Pennsylvania. Data collection entailed a participatory mapping exercise in which individual students were instructed to use stickers to mark locations on a blank campus map where they had experienced gender-based violence. Different color stickers indicated different types of harm (e.g., sexual assault, verbal harassment, unwanted touching, stalking, physical abuse, and feeling vulnerable to experience gender-based violence). In addition to better understanding where on campus the student body has experienced gender-based violence, a secondary objective of the project includes providing recommendations to Lafayette College administrators regarding ways to modify the built environment to help prevent future harm from occurring. To support these objectives, the research team began working with Lily Houtman, a trained cartographer, to incorporate feminist design principles into the mapping of the project’s data for public-facing audiences. Here, we describe our design process and share takeaways for cartographers working on similar projects.

Abstract When the Age-Friendly University (AFU) Taskforce at the University of Colorado Anschutz Medical Campus initiated strategic planning in 2023, the built environment – an antecedent condition for achieving AFU priorities – emerged as priority #1. The taskforce tailored an existing tool available from University of Massachusetts-Boston to align the built-environment assessment with the broader mission-focused areas of CU Anschutz – one of the first four academic medical campuses in the world to receive the AFU designation. During April 2023, each taskforce representative paired with an older adult community member; each dyad was assigned a campus zone to assess using the adapted Age-Friendly Inventory and Campus Climate Survey. The community member provided first-hand accounts of how they experienced aspects of the built environment, while the taskforce representative recorded observations. Once compiled, the taskforce reviewed data and identified the following areas of concern: wayfinding supports (e.g., signs and campus maps -- printed, online); parking kiosk accessibility; distances (e.g., from parking to campus buildings); campus building and restroom accessibility. Taskforce members presented results and recommendations to the Chancellor, campus architect, Vice Chancellor for Facilities, and Communications team. Through campuswide collaborations that expanded to include parking managers and the campus shuttle service, issues with campus maps, parking kiosks, crosswalks, walking distances, and building/restroom accessibility are being addressed, with a progress report provided to the Chancellor in July 2024. This work is essential. The built environment fundamentally influences campus accessibility across the lifespan and the age-inclusivity of events, classes, research studies and healthcare services.

Abstract Currently, the campus area is gradually expanding with the increasing number of university students. Consequently, it is difficult for freshmen or visiting staff to find a specific building at the campus. The aim of the study was to Develop Campus Web GIS Navigation System of the study area by using Geospatial technology. This research is mainly design to carry out the campus navigation of study area to provide better understanding of campus environments to all the stake holders like students, technical support staffs, academic staff, administrative support staffs and unfamiliar. Not only this but also used for integrating up to date information into campus navigation that will be used by concerned authorities to make any developmental plans and implement policies and programs. The general procedures to create web map navigation application are Geo-referencing Image, digitization, Road Network Analysis, Overlay Analysis and finally, a Web GIS Based Campus Navigation System has developed. The main activity of the system application is the map activity. It displays the campus map of the Wachemo University. The user can zoom and scroll this map to get his/her desired places. The building map is the basic layer of this screen. The end user can access by using thislink:https://wcu-webmap.github.io/Web-Map-of-WCU/

Abstract: Campus maps and architectural images from institutional websites were used to compare 45 collegiate institutions cited in prior literature as manifesting traits of either conventional or nonconformist student cultures. Based on person–environment interaction theory, it was anticipated that the physical traits of campuses associated with conventional student cultures would be more uniform than those of campuses associated with nonconformist student cultures. Nonparametric tests revealed significant differences in the anticipated direction on three of six aspects of architectural design (i.e., color, roofline, and ornamentation). Differences in uniformity of campus layout were in the anticipated direction but fell slightly short of statistical significance.

A problem of navigation within large educational complexes has been identified, which poses a particular challenge for new students, visitors, and staff. It has been established that the implementation of augmented reality technologies considerably enhances the intuitiveness and usability of the navigation system. A comprehensive structural and mathematical model of the navigation system based on augmented reality technologies has been meticulously developed. This model formalizes the functional dependencies among the system components, enabling a deeper analysis of interconnections and optimization of operational processes. The working algorithm of the system, which utilizes cutting-edge augmented reality technology, is thoroughly described. A software solution for navigating between university buildings, using advanced augmented reality technology, has been developed. This system simplifies the spatial orientation within the campus during transitions between buildings, significantly enhancing the user experience. An interface that seamlessly combines intuitive understanding with visual attractiveness has been proposed, aiding users in effectively planning their academic day. Additionally, the system includes a module that provides visitors with essential information about respective university buildings and access to class schedules. The system architecture comprises several key blocks: the sensor block, the software and data processing block, the campus map integration block, the user interface block, and the interaction and personalization block. These components together ensure a seamless and personalized user experience. The design of the components has employed a systematic approach that ensures interface personalization, stringent data security, and efficient user interaction. In developing the application, the Kotlin programming language, MVVM architectural pattern, Dagger 2 libraries, and the ARCore platform for augmented reality, specifically tailored for the Android platform, were utilized. These technologies provide flexibility, scalability, and efficiency in development. Future research directions have been proposed, which include the further refinement of the software and the expansion of the system's functionality. Additional modules are planned to be developed to meet the evolving needs of the student body and staff of educational institutions, thus enhancing accessibility and integration with other information systems of the educational establishment.

ABSTRACT A range of structural, interpersonal and individual factors contribute to the extent to which people can access higher education and experience inclusion and equity once there. This paper considers the experiences of parents in higher education settings, and examines the extent to which universities in two countries support parents’ inclusion through the facilities and services evident on their campus maps. The inclusion of such parent-related facilities and services on campus maps reflects not only a commitment to providing support infrastructure, but importantly to making them visible, promoting a culture of normalisation of parents and parenting in higher education. We used manifest content analysis to examine the campus maps of Australia’s n = 37 and New Zealand’s n = 8 public universities, with a total of 281 distinct physical sites identified. Childcare services, parents’ rooms, baby change tables, nursing areas and parking-related services were identified, although the prevalence within and across sites varied greatly. A lack of clarity in labelling and inconsistency across different modes of maps pose barriers to access and visibility in some cases, and overall, reporting of parenting-related infrastructure was limited. Our analysis indicates that parents attending university campuses may face ongoing challenges as they navigate their dual academic and parenting responsibilities.

The "Smart Cities" concepts have been adapted to several environments, to bring technology usage at infrastructure, planning, management, and people levels, in specific geographic space and time. UCM -University Campus Map [1]is a smart campus initiative developed by Paraná Federal University, which provides geographic information -indoor and outdoor -applied to university campus usage. Data from UCM become an official university base map, considering several contexts of use and diverse necessities, from several actors. Also, the project supplies map interfaces that take into account navigational, querying, visualization, and interaction with all different environments from the University resources and facilities. Cartographic products associated with UCM such as interactive 3D and 2D maps, street view (SV) based maps, and egocentric perspective maps, can represent large volumes and types of data, including the provision of data incorporation coming from sensors and those collected from collaboration (VGI data) or gathered from social media. Recently, Street View imagery (SVI) data became popular form of a navigational and ground-level data source [3]. With a level of detail similar to virtual environments, it is possible to integrate photographic information with map perspective, creating an interactive display that offers some degree of immersion. There is potential to integrate powerful map interfaces, together with 2D interactive maps, for spatial awareness and navigational tasks. Although studies with SVI data are common and have many applications [3][4], their use is yet to be more understood, especially from the point of view of interface usability, cartography, and potential contexts of navigation and other utilization. The Federal University of Amazonas (UFAM) is a collaborating partner in the UCM project, situated in the Brazilian Amazon. The university's primary campus, spanning over 650 hectares of natural terrain, is located in Manaus (AM), within a protected area and comprises a rainforest fragment, comprising approximately 20% of constructed buildings and facilities. The campus witnesses a daily footfall of nearly 15,000 individuals, including both internal and external stakeholders. With over 20 river sources, 12 water streams, and 29 forest trails, UFAM conducts several scientific research initiatives in biology, forest engineering, environmental conservation, and other fields such as health, physical education, urbanism, and tourism. The university's campus also experiences social pressure from neighboring communities, posing regular concerns regarding security, transportation, and general management. Given the scale and diversity of usage and interest in conservation, mapping the study area is a challenging task. We believe that the map interfaces and database solutions provided by UCM would be invaluable to the community and the managers. This research, as a mapping study, specifically focuses on aiding the university audience and users in navigating the campus's indoor and outdoor environments. As suggested by the survey on user requirements, this context is essential as the project seeks to identify potential community products, technologies, and procedures. This research proposes an experimental study to provide insights into the usage and interaction of an SVI + map interface, primarily concerning locating real-world features and navigation within the university context. The qualitative map study design seeks to address the following research questions: 1) Does the audience exhibit an interest in such an interface? 2) Is it feasible and attractive for users? 3) What potential issues may arise? 4) What are the implications of using SV imagery compared to conventional map apps and webmaps in terms of learnability and usability? The research focuses on officebased tasks, primarily related to planning routes. The ongoing work addresses in-situ navigation and its associated challenges. Moreover, users are currently being recruited for a quantitative analysis to assess the performance and accuracy of the interface, considering desirable positioning, routing, and landmarks' memorability. We provided a simple interface with SVI (the open-source mapillary frame) dividing the screen with a traditional OpenStreetMap frame, linked by a point symbol. Users had to accomplish tasks representing common usage from the perspective of student and campus service providers, with low to high familiarity with the area. One task example was

In this study, the faculty network system was designed using the Cisco Packet Tracer program without using any physical components. The aim was to simulate the network structure of the faculty and show the engineering faculty on the campus map, and to enable communication between the computers inside the faculty by configuring similar devices to real routers, switches, and servers. The management of the IP configuration of the devices in the network, and the configuration of the router, switch, and server used in the network (DNS, DHCP, FTP, HTTP, and MAIL) were carried out in the Cisco Packet Tracer environment, creating a simulated network system that can be applied in a real system.

Software Smart Agent for Taif University Services

The ability to create an accurate mental survey representation, orcognitive map, when moving through an environment varies widely across individuals, and we are still trying to understand the origins of these individual differences. Non-immersive virtual environments used to test for cognitive map accuracy in the laboratory have shown sex differences with a performance advantage for men in some studies but not others. When sex differences are demonstrated, it is unclear whether women’s performance generalizes to familiar and unfamiliar real-world environments. In Experiment 1, 98 participants explored the virtual environment Silcton and afterwards estimated directions between the landmarks in Silcton and arranged landmarks found in Silcton on a map. In addition, they reported frequently visited real-world locations and then estimated directions between them and drew a map of the locations. Men were more accurate on tests of Silcton than women were, although there was no difference between sexes for accuracy with real-world locations. Within sexes, women were more accurate with the real-world locations than Silcton, while men showed the opposite pattern. In Experiment 2, 21 women were tested with Silcton and their familiar real-world locations as in Experiment 1 but were also walked through an unfamiliar real-world area on campus and completed direction estimation and map drawing tests for the new environment. Overall, women were more accurate with the two real-world environments than Silcton, with some evidence that accuracy with the new real-world environment was more accurate than the familiar real-world locations. Overall, women’s ability to create a cognitive map of a virtual environment in the laboratory does not seem to be indicative of their ability to do the same in the real world, and care should be taken when generalizing lab results with virtual environments.

Abstract 3D technology is used in GIS maps to create descriptive graphics that accurately depict the size of real-world items. In a wide variety of various areas, 3D models aid in appearance and survey. For example, 3D maps may depict the height of a building or a mountain in addition to its location. 3D tools must be utilized in conjunction with 2D GIS and then visualized in a 3D environment. The current UPNM campus map accessible to students and staff is not sufficiently helpful and hardly identified its whereabouts. This project was undertaken to develop a web-based 3D campus map and analyze specifically the campus’s area zoning. This study uses a personal computer with Esri CityEngine software to develop the 3D campus map and ArcGIS Online to publish the web-based 3D campus map. The data was acquired by downloading the base map of UPNM from OpenStreetMap (OSM). Completion of data processing results in a web-based 3D UPNM campus map with area zoning. The finding shows that the 3D map, using the Geographical Information System (GIS) platform, is more informative and attractive than the 2D map due to the attribute and spatial data. In addition, the capabilities of the 3D map to visualize and show the campus area and area zoning in the map can be managed according to the structural information. All in all, it can be concluded that this web-based 3D map contributes towards the sustainability of the UPNM infrastructure and campus while facilitating campus maintenance and rehabilitation.

Report of the Eighty-Third Annual MeetingSan Diego, California October 14–16, 2021 Liz Ridder, Atsushi Nara, and Yolonda Youngs (bio) After a one-year meeting hiatus due to Covid-19, APCG members gleefully gathered, in-person and online, for the Eighty-Third Annual Meeting at San Diego State University (SDSU). Much to the organizers' relief, 149 people pre-registered for the meeting, with 66 online and 83 in-person attendees, plus several folks who registered in person. This year's meeting was unique for many reasons and was aptly themed "Geographies of Transition." Organizers Atsushi Nara, Liz Ridder, and Yolonda Youngs, each from a different California State University (CSU)—SDSU, CSU San Marcos, and CSU San Bernardino—banded together to bring a hybrid meeting format to APCG without losing long-standing APCG meeting traditions. This "experimental" year was part of a larger initiative organized by the AAG and its Climate Action Task Force as part of their Regions Connect: A Joint Climate Forward Initiative, which may lead to larger regional meetings in the future, to reduce carbon emissions of AAG events. As part of meeting registration, attendees could virtually attend the streaming and recorded sessions of the Applied Geography Conference and the AAG Regional Division meetings of the Southwest (SWAAG), East Lakes, West Lakes, New England-St. Lawrence Valley (NESTVAL), and Great Plains/Rocky Mountains. Concurrent paper and poster sessions took place Thursday and Friday in the Conrad Prebys Aztec Student Union. Also known as the Union, the building opened in 2013, replacing the first CSU student union, the Aztec Center. The construction of the Union reused and recycled approximately eighty percent of the Aztec Center's materials, and the building is LEED Double Platinum Certified. The recent renaming of one of the meeting rooms created momentary confusion until a clever geographer updated the door sign to match the new name printed in the meeting program and campus maps. Once [End Page 163] meeting room locations were sorted, thirty-one in-person and seventeen virtual papers and eight posters were presented by authors from Arizona, California, Michigan, Washington, Oregon, Nevada, Florida, Alabama, and Germany. On Thursday afternoon, Keynote Speaker Dr. Marilyn Raphael, Professor, UCLA, Director of the UCLA Institute of the Environment and Sustainability, and Vice President of the AAG, presented "Antarctic Sea Ice—How Important Is It?" highlighting regional patterns of spatial, spectral, and temporal variability, including the timing of advance and retreat, and positive and negative growth trends of sea ice throughout the Antarctic. These patterns are likely related to Antarctica's geography and the influence of the ocean and atmosphere, which are expected to change as the atmosphere continues to change. Friday's Keynote Lecture by Dr. Park Williams continued discussions on "Geographies of Transition" and the impacts of climate change in his talk, "The effect of climate change on water, wildfire, and life across North America." This year's conference also featured two special sessions on Friday afternoon. Dr. Atsushi Nara organized and moderated a hybrid-mode interactive workshop to identify perceptions about the skills and knowledge to succeed in geocomputation-related careers. The project is an NSF-funded collaboration through an Encoding Geography Researcher-Practitioner Partnership (RPP) led by AAG, SDSU, San Diego Mesa Community College, Sweetwater High School Union District, Texas State University, and UC Riverside. Dr. Dan Arreola organized and moderated a discussion panel titled "Donald W. Meinig's Southwest at Half-Century, A Reflection and Appreciation." Former Meinig students and scholars of his work Bill Wyckoff, Craig Colten, Paul Starrs, and Richard Nostrand shared their perspectives on Meinig's influence on their interpretations of the Southwest and the formation of their geographical perspectives. Social events such as the Women's Network and Graduate Student lunches provided opportunities to celebrate students and connect with new colleagues and old friends. The Thursday-night reception on the Union's 3rd Floor Terrace included wonderful food and drink, supplemented [End Page 164] by a spectacular view and live music from the courtyard below. The highlights of Friday night's awards banquet were the numerous student awards for outstanding papers and posters and student travel scholarships, presenting Chris Lukinbeal with the Distinguished Service...

The main purpose of this study is to design and develop “Süleyman Demirel University Campus Maps system (SDU Campus Maps)” with geographic information systems in order to create a campus information system. By the contribution of SDU Campus Maps, which is planned to be carried out, directions will be provided from one point to another within the university, and it will be convenient for visitors who do not know about Süleyman Demirel University campus. With this idea, it is based on the preparation of the environment so that directions can be made using the SDU campus map. With the help of this study, it has been aimed to provide contribution to the literature of both geographic information systems and mapping.