AbstractIn recent years, Japan has assisted in technique and capacity development for bridge maintenance and management in developing countries worldwide. Such projects are aimed at formulating maintenance and management plans, which include bridge inspection and repair techniques. However, because the current conditions of the bridges to be managed are not well understood, most developing countries have no effective data available for formulating bridge maintenance and management plans. To this end, the authors introduce a bridge database system that uses smartphones to collect bridge inventory data and implements a brief bridge inspection to help formulate bridge maintenance and management plans as a part of technical-assistance projects supported by the Japan International Cooperation Agency in Kenya, Madagascar, and Tajikistan. Furthermore, a bridge database system that includes bridge inventory and inspection records can be established automatically during data collection and inspection work without any additional effort. This system is expected to contribute toward establishing a bridge database system in countries that have no inventory data or inspection records.IntroductionBridges are an integral part of modern highway infrastructure. In Japan, there are approximately 700,000 road bridges, and a considerable proportion of this road infrastructure was constructed during the high economic growth period of the 1970s and 1980s (Ministry of Land, Infrastructure, Transport, and Tourism of Japan 2014). The Ministry of Land, Infrastructure, Transport, and Tourism of Japan (MLIT) has estimated that over 40% of bridges in Japan will be over 50 years old in 2023 (Ministry of Land, Infrastructure, Transport, and Tourism of Japan 2014). To respond to this situation, MLIT, research institutes (such as the Public Works Research Institute), local governments, educational institutions (such as universities and national institutes of technology), and private companies have thoroughly investigated technological developments related to bridge maintenance and management works (Cabinet Office of Japan 2021). In addition, public concern regarding the maintenance and management of road infrastructures such as bridges and tunnels has continued to increase in the wake of the Sasago tunnel collapse in 2012.Many technical cooperation projects concerning the maintenance and management of roads and bridges have been implemented in Asia and Africa with the support of aid agencies such as the Japan International Cooperation Agency (JICA) and Asia Development Bank (ADB). Projects for the capacity development of bridge maintenance and management supported by JICA after 2015 are listed in Table 1. Because these technical cooperation projects have been implemented based on requests from each country, it is clear that technology for the maintenance and management of roads and bridges has attracted attention in both developed and developing countries.Table 1. List of the works under the Project for Maintenance and Management of Bridges Supported by JICA since 2015Table 1. List of the works under the Project for Maintenance and Management of Bridges Supported by JICA since 2015CountryDuration (months)Project title Sri Lanka2015–2017 (36 months)Project for Capacity Development on Bridge Management Bangladesh2015–2018 (32 months)Bridge Management Capacity Development Project Cambodia2015–2018 (37 months)Project for Strengthening Capacity for Maintenance of Roads and Bridges Pakistan2016–2018 (34 months)Project for Technical Assistance on Implementation of Bridge Management System in National Highway Authority Philippines2016–2019 (39 months)Improvement of Quality Management for Highway and Bridge Construction and Maintenance Phase 3 Bhutan2016–2020 (45 months)Technical Cooperation Project for Capacity Development in Construction and Maintenance of Bridges Laos2020–2023 (36 months)Project for Capacity Development on Bridge Maintenance and Management Myanmar2020–2022 (30 months)Project for Capacity Development of Road and Bridge Operation and Maintenance Tajikistan2021–2024 (44 months)Project for Capacity Development for Bridge Management Zambia2015–2023 (72 months)Project for Improvement of Bridge Maintenance Capability Building (Phase 1 and Phase 2) Ghana2019–2023 (48 months)Project on Capacity Building for Road and Bridge Management Kenya2020–2025 (60 months)Project for Strengthening of Capacity Development on Bridge Management System Madagascar2021–2024 (45 months)Project for Capacity Development for Road and Bridge Maintenance Mozambique2021–2024 (42 months)Project for Improvement of Bridge Maintenance and Management CapabilityAs a member of the JICA expert team, Watanabe has participated in several projects on the maintenance and management of roads and bridges in Kyrgyzstan, Cambodia, Myanmar, and Kenya that focus on bridge inspection, bridge soundness diagnosis, and database development. The author is presently studying bridge inspection and inspection record management methods that consider the actual conditions in developing countries.This paper describes the challenges for bridge maintenance and management in developing countries and introduces a system for bridge data collection developed by the authors and implemented in several actual projects. Then, an improved bridge data collection system widely applicable in developing countries is proposed alongside a utilization method for the data obtained by the developed system.Literature Review and Bridge Maintenance CycleThe JICA conducted a Study on Technical Cooperation Projects for Bridge Maintenance and Management to Developing Countries (hereafter, the JICA Project Study) in 2019 (JICA 2019). The resulting report reviewed technical cooperation projects on bridge maintenance and management that Japan has participated in during 2007–2018 (covering 12 countries: the Philippines, Thailand, Mongolia, Kyrgyzstan, Sri Lanka, Bangladesh, Cambodia, Pakistan, Ethiopia, Egypt, Zambia, and Bolivia), identified the issues observed in each project, and summarized the points to be considered in future technical cooperation projects.According to the JICA Project Study, the general issues faced by developing countries regarding the maintenance and management of bridges can be summarized as follows: •lack of staff in the governing organization,•shortage of budget for maintenance and management work on bridges,•lack of specialized knowledge about bridges,•lack of previous bridge inspections, and•lack of official and collective bridge inventory data.Watanabe et al. (2021) listed specific challenges for bridge maintenance and management in developing countries based on the JICA Project Study and personal experience while working on JICA-supported technical cooperation projects as follows: •lack of data/records that help to understand the status of the bridge (location, bridge length, bridge type, construction year, current condition, and so on),•lack of daily and/or periodic bridge inspections,•nonuniform bridge inventory and inspection data records and format, if data/records exist,•no bridge maintenance plans formulated based on bridge data, and•very little repair of bridges has been conducted.The preparation of bridge maintenance and management plans, which includes budgeting, is one of the objectives of JICA’s assistance projects. However, as pointed out by Henry et al. (2018), existing bridge information and unified records describing basic information and inspection results, which form the basis of bridge maintenance and management plans, are almost nonexistent in developing countries. Furthermore, it has been reported that even when bridge databases are established with the support of aid agencies, input into such databases is typically considered the responsibility of counterparts in the developing countries after the project is completed; in many cases, the data are not entered and the database does not function. Indeed, Henry et al. (2018) reported that data for 720 bridges in Myanmar were supposed to be entered after a JICA technical cooperation project; however, when the author checked in 2020 during a subsequent project supported by JICA, they were still not entered.The bridge maintenance workflow follows a cycle that involves inspection, diagnosis, and development/implementation of a maintenance management plan. Inventory data and condition assessment through bridge inspection are prerequisites for bridge maintenance management. Fig. 1 shows a bridge maintenance cycle proposed by Watanabe et al. (2021). Anwar (2010) proposed that inventory and condition assessment are essential components in bridge maintenance work. Furthermore, Mohammed et al. (2020) cited Anwar (2010) maintenance cycle in their paper on measures to enhance bridge maintenance in Nigeria. Both cycles, namely Watanabe et al. (2021) and Anwar (2010) to be cited by Mohammed et al. (2020), start with inventory and inspection or condition assessment, as indicated. Therefore, it can be said that the bridge maintenance cycles presented in these papers have become standard conceptual diagrams for bridge maintenance businesses.Thus, as indicated in the preceding paragraphs, bridge asset management and maintenance have received unprecedented attention in recent years, not only in developed countries but also in developing countries (Road Infrastructure Department, Ministry of Public Works, and Transport in Cambodia 2017). Road networks are among the most important infrastructures for a healthy economy and the development of a country/region because they typically facilitate the highest proportions of passenger travel and logistics; thus, road hazard events are critical in terms of evaluation, response, and recovery. However, in many developing countries, there are no/limited existing bridge inventory and inspection data, nor is there a bridge database. Thus, bridge data must be collected from scratch to serve as fundamental information for the preparation of a bridge maintenance and management plan.Although previous studies have focused on the functional aspects of bridge databases and sophisticated data use (deterioration prediction, life cycle cost calculation, and so on), most have assumed that bridge data are accurately input or have used pre-existing bridge databases. Because bridge inventory data are essential for efficient bridge maintenance and management, the first step in developing countries is the collection of such data. As a result, discussions and methods are required to design approaches to quickly collect and input bridge data into a database system to build an initial database.One representative example of readily available bridge inventory data is the US road bridge data provided on the internet by the US Federal Highway Administration (FHWA, n.d.) as the National Bridge Inventory. Researchers belonging to universities and research institutes can use such databases along with bridge owners to actively pursue technological developments related to bridge maintenance. For example, Alogdianakis et al. (2020) performed a data analysis to extract structural deterioration information from a bridge inventory database containing more than 500,000 bridges maintained by the FHWA. Morcous et al. (2010) demonstrated two approaches to predict the deterioration of concrete bridge decks at two management levels of an integrated system using condition assessment data obtained from the database of the Quebec Ministry of Transportation and a condition assessment of the Dixon Bridge in Montreal, Canada. In Japan, Kobayashi et al. (2022) created salt damage, frost damage, and alkali-silica reaction damage distributions based on bridge inspection data collected by fiscal year 2019 from concrete bridges administrated by the MLIT to clarify how the environment affects concrete bridge durability.However, these studies relied upon extant bridge inventory and inspection data; they did not need to collect it. In developing countries where there is no comprehensive bridge data, it is necessary to first compile a database of inventory and initial inspection data; however, few studies have investigated bridge data collection on a global scale. In addition, bridge data have not been collected from several thousand bridges on a national scale to the best of the authors’ knowledge; there is clearly a lack of practical studies focusing on this issue.Therefore, the authors developed a simple, quick, accurate, and efficient method to collect bridge inventory and inspection data for the future development of a bridge database system. This system was then trialed in developing countries. In the proposed system, the information obtained at the site—e.g., bridge inventory data (such as the bridge length, type, and location) and bridge inspection results—is recorded using smartphones and integrated on a server to automatically develop a bridge database.Bridge Database SystemSystem Development ConsiderationsConventionally, bridge inspection work is conducted using simple field tools. The inspector manually writes the inspection record in a sketch book, drawing, inspection sheet, and so on at the site. After returning to the office, the field information is re-entered into digital inspection forms, which are normally Microsoft Excel files stored locally on a computer and printed out to serve as the inspection report; however, this approach is inefficient because it involves double recording.Table 1 indicates that JICA typically assists in projects related to bridge maintenance and management capacity development for periods of 3–4 years. During these periods, data such as bridge inventory and inspection results must be collected, the bridge conditions must be assessed, and the bridge maintenance plan must be formulated. Because the latter half of the project must focus on developing a bridge maintenance plan and calculating the bridge maintenance budget, the collection of bridge data must be completed within the first year of the project.Therefore, it would be difficult to collect all inventory and inspection data for bridges in an entire country and build a bridge database during the project period using the conventional bridge inspection and data recording method. To address this issue, the author referred to a bridge inspection method using tablet computers developed by Ibayashi et al. (2013) and applied in Cambodia by Watanabe et al. (2021) to propose a system that can collect bridge data and build a database using smartphones, making it globally applicable.During their practical study in Cambodia, Watanabe et al. (2021) reported that tablet computers used in a high-temperature environment frequently crashed because of high internal temperatures. To address this and other issues, the following points were considered to enable the easy, rapid, accurate, and efficient collection of bridge data: •Information that can be obtained using built-in smartphone functions [e.g., bridge location can be obtained using the Global Navigation Satellite System (GNSS) function] should be obtained automatically to reduce input errors and time.•The spelling of information can differ between English-speaking and non-English-speaking countries because words are often converted from the sound of the official national language to alphabetic notation. Therefore, for predetermined items such as region names, road names, and materials, a pull-down list and/or check-box style should be used to provide quick input and to ensure searchability in the future.•Empty cells should be highlighted in red to prevent omissions.•Items to be entered numerically such as bridge length and width should be input using the numeric keypad; only decimal points (as opposed to commas) should be used to prevent interpretation errors owing to the different meanings of commas and decimal points in different countries.•Bridge inspections require visual inspection while moving from one end of the bridge to the other and from the bridge surface to the ground around the substructures; therefore, the system configuration should not require multiple trips back and forth.The system introduced in this paper is essentially an updated version of the Watanabe et al. (2021) system applied in Cambodia. Further, considering the reality of developing countries, where connectivity can be weak in rural areas, the following points were considered: •, which is an offline map application that can be used even in areas with a weak network connection, was adopted to identify the bridge locations on a map on the smartphone.•The information recorded at the site is temporarily stored in the smartphone without requiring any data communication; it can then be transmitted to the data server when a strong network connection is available.Structure of the SystemThe proposed system operates via smartphone as the client device. A smartphone has built-in capabilities such as a camera, GNSS, text input, data storage, sound recorder, and data communication. This enables the simultaneous development of a bridge database system while conducting and recording the results of bridge inspections onsite. Data recorded at the bridge site can then be sent to the data server from the smartphone.The system is based on the FileMaker series version 13 software for database development; the iPhone device series serves as the client device operated by the inspector recording the data at the site. The iPhone was adopted because it has common specifications worldwide as well as many language settings. Furthermore, a computer with MacOS running a FileMaker server was used as the database server. If the server is installed in a location with an unreliable power supply, it is preferable to adopt a laptop computer that does not turn off immediately in the event of a power outage to prevent data loss. A schematic of the system configuration is illustrated in Fig. 2.The system file consists of two features: (1) an inventory system, and (2) a brief inspection system; the data in both systems are linked by the bridge ID allocated by the inventory system, as indicated in Fig. 3. The basic operation flow of the system involves preparing the inventory data using the inventory system, after which the inspector inputs data (general data, superstructure, pavement, slab, substructure, and so on) by performing measurement work and taking photos at the site. Next, the brief inspection system is launched to conduct the bridge inspection. There are five preset inspection categories: road surface, superstructure (including the deck slab), abutment, pier, and around bearing. The operational flow of the system is summarized schematically in Fig. 4.Data describing the bridge inventory and inspection recorded at the site can be communicated from the iPhone client device to the database server using the mobile data connection. However, it is assumed that a large quantity of data will be generated owing to the many photos included, making it difficult to send the data from the site using the mobile data connection, especially in rural regions in developing countries where high-speed data communication networks may not be established. Therefore, another version of the system, called the offline version, was prepared for such scenarios. In the offline version, the data recorded onsite are temporarily stored on the iPhone. When it becomes possible to connect to the internet through a high-speed data communication network, the data stored in the iPhone are transmitted to the server. This system is designed for use with the iPhone but can also be used with an iPad if a larger screen is desired.Inventory Data SystemThe inventory data system requires information fundamental to the preparation of a bridge maintenance and management plan. For example, it requires bridge dimensions (bridge length, width of carriage way, and width of sidewalk), location (coordinates automatically acquired by GNSS), material, structure type, existence of bridge accessories (bearings, expansion joints, and so on), and photos. The items recorded in the inventory data system are listed in Table 2, and the data input procedure is illustrated in Fig. 5.Table 2. Fundamental items in inventory data systemTable 2. Fundamental items in inventory data systemInventory data itemInput methodBridge nameKeyboardArea 1 (state/county/province, and so on)PulldownaArea 2 (city/town)PulldownaRoad categoryPulldownaKP (kilometer + meter)NumpadAdministratorPulldownaLocation 1-latitudeAutomaticLocation 2-longitudeAutomaticBridge lengthNumpadNumber of spansNumpadMaximum span lengthNumpadBridge width (including curb)NumpadCarriageway widthNumpadSidewalk width in leftNumpadSidewalk width in rightNumpadNumber of lanesNumpadConstructed year (if unknown, blank)NumpadMaterialPulldownMaterialPulldownStructure typePulldownNumber of girder per one spanNumpadContinuousPulldownMaterialPulldownMaterialPulldownStructure typePulldownFoundation typePulldownHeight of A1NumpadHeight of A2NumpadMaterialPulldownStructure typePulldownNumber of columns per pier (if multiple columns)NumpadDimensions (rectangular)NumpadDimensions (circle)NumpadBearingCheckboxExpansion jointCheckboxBridge railing/guard fenceCheckboxAppurtenances (electric cable, communication cable, and so on)CheckboxRoad surfacePhotographyOverviewPhotographyUndersidePhotographyName platePhotographyData preparation dateAutomaticThe inventory data input method comprises five screens on the client device, as shown in Fig. 5. The first screen [Fig. 5(a)] indicates that three photos of the bridge should be taken: a general view, the road surface on the bridge, and the bridge nameplate. The location information (longitude and latitude) can be passed to the external application by pressing the Map button in the upper right corner to check whether the latitude and longitude are approximately correct. The second screen [Fig. 5(b)] is used to input general information such as the bridge name, road category/class, and road administrator; the latitude and longitude are entered automatically. Even if the inspector forgets to check the bridge location on the map on the first screen, the Map button is placed in the same position on the second screen so that location can still be confirmed. The third screen [Fig. 5(c)] is used to input additional general information such as bridge length, width, number of spans, and year of construction. The fourth screen [Fig. 5(d)] is used to enter information describing the superstructure such as pavement type, superstructure material, structural type, slab material, bearing and telescopic device information, and presence or absence of attachments.The fifth and final screen [Fig. 5(e)] is used to input information describing the substructure; the inspector takes a photo from underneath the bridge and enters several items regarding piers and abutments. After these inputs are completed, the bridge inventory sheet shown in Fig. 6 is automatically generated, and the data are stored on the client device. This inventory sheet can also be emailed directly from the client device as a PDF file.The four pull-down items in Table 2 (Area 1, Area 2, Road category, and Administrator) can be replaced according to the specifications of each country, making this system globally applicable.Brief Inspection SystemAfter preparing the inventory data, the bridge inspection commences using the brief inspection system to record information describing the structural soundness of the bridge. The smartphone-based input method is used to guide the inspector to check for existing damage in accordance with the inspection items displayed on the screen (Table 3). If damage is found, a situational photo is captured using the camera built into the iPad/iPhone. If an anomaly that cannot be reported with a photo is found, such as an abnormal sound at an expansion joint, this sound can be recorded using the built-in microphone. Thus, it is possible to report damage that could not be previously recorded using paper documentation. Furthermore, these inspection data, including damage situation photos and sound data, can be managed on the same platform.Table 3. Inspection items, damage points, evaluation score, and weights of members in brief inspection systemTable 3. Inspection items, damage points, evaluation score, and weights of members in brief inspection systemElementInspection itemPointsDamage level (DL) I to IIIScore in member, AWeight of member, B (%)MaterialPositionRoad surfaceRoad surfaceRoad surfaceRutting on pavement11–2 points: DL I, 3–5 points: DL II, and 6 points and over: DL IIIDL I: 1, DL II: 3, and DL III: 510Cracks on pavement1Lack of curb1Rebar exposure on curb2Damage on railing/side barrier3Collapse of railing/side barrier6Damage on expansion joint3Clogging drainage3SuperstructureSuperstructureConcreteCracks21–3 points: DL I, 4–7 points: DL II, and 8 points and over: DL IIIDL I: 1, DL II: 3, and DL III: 530Free lime1Rust fluid3Honeycomb2Delamination5Rebar exposure5SteelPaint peeling21–4 points: DL I, 5–9 points: DL II, and 10 points and over: DL IIICorrosion4Rust2Cracks5Deformation3Section loss3Fracture5Missing bolts3WoodenRots31–2 points: DL I, 3–4 points: DL II, and 5 points and over: DL IIICracks2Falling off of member5MasonryCracks21–3 points: DL I, 4–6 points: DL II, and 7 points and over: DL IIISection loss2Misalignment2Falling off2Deformation3Deck slabConcreteCracks21–4 points: DL I, 5–9 points: DL II, and 10 points and over: DL IIIDL I: 1, DL II: 3, and DL III: 510Free lime1Rust fluid3Honeycomb2Delamination5Rebar exposure5Falling off5SteelCorrosion31–4 points: DL I, 5–9 points: DL II, and 10 points and over: DL IIIRust2Cracks5Deformation3Section loss4Fracture5WoodenRots31–2 points: DL I, 3–4 points: DL II, and 5 points and over: DL IIICracks2Falling off of member, hole5AbutmentAbutmentConcreteCracks21–4 points: DL I, 5–9 points: DL II, and 10 points and over: DL IIIDL I: 1, DL II: 3, and DL III: 520 (but 40 if single span)Free lime1Rust fluid3Honeycomb2Delamination5Rebar exposure5Settlement/scouring10MasonryCracks21–4 points: DL I, 5–9 points: DL II, and 10 points and over: DL IIIBig gap2Falling off of stone3Deformation3Settlement/scouring10WoodenRots31–2 points: DL I, 3–4 points: DL II, and 5 points and over: DL IIICracks2Settlement/scouring5PierPierConcreteCracks21–4 points: DL I, 5–9 points: DL II, and 10 points and over: DL IIIDL I: 1, DL II: 3, and DL III: 520Free lime1Rust fluid3Honeycomb2Delamination5Rebar exposure5Settlement/scouring10SteelCorrosion31–4 points: DL I, 5–9 points: DL II, and 10 points and over: DL IIIRust2Cracks5Deformation3Section loss4Fracture5Settlement/scouring10Concrete and steelCracks on concrete member21–4 points: DL I, 5–9 points: DL II, and 10 points and over: DL IIIFree lime1Rust fluid2Honeycomb1Delamination of concrete3Rebar exposure3Corrosion3Rust2Cracks4Deformation2Section loss3Fracture4Settlement/scouring10WoodenRots31–2 points: DL I, 3–4 points: DL II, and 5 points and over: DL IIICracks2Settlement/scouring5MasonryCracks21–2 points: DL I, 3–6 points: DL II, and 7 points and over: DL IIIBig gap2Falling off of stone2Deformation2Settlement/scouring7Around bearingAround bearingBearing and joint gapSedimentation21–4 points: DL I, 5–9 points: DL II, and 10 points and over: DL IIIDL I: 1, DL II: 3, and DL III: 510Rust3Puddle of water2Functional impairment5Slipping out5Abnormality at joint gap4Watanabe et al. (2021) established a bridge database for the Ministry of Public Works and Transport in Cambodia under the Project for Strengthening Capacity for Maintenance of Roads and Bridges supported by JICA using a similar system (Japan International Cooperation Agency 2019); however, the system checked for the existence of damage for each inspection item in a predetermined order: road surface, superstructure, deck slab, bearing area, and then substructure. This inspection approach had notable usability issues. For example, the bridge inspection always had to start from the road surface, and if damage was found in the deck slab during the substructure inspection, it was necessary to return to the relevant damage item in sequence. Thus, the authors improved the system to enable the inspector to begin the bridge inspection from the easiest point after preparing the inventory data, regardless of their location. In addition, the system was upgraded to cover masonry bridges in reference to the inspection guidelines for masonry bridges in Oita Prefecture, Japan (Oita Prefecture 2021).Bridge components were categorized into the five elements shown in the Element column of Table 3, and inspections and records are completed based on these elements. This allows for the inspector to navigate among elements as they are observed, for example starting from the substructure at the completion of the inventory preparation, eliminating the need to first return to the road surface, as was necessary in the system described by Watanabe et al. (2021). Eliminating unnecessary movements of the inspector not only saves inspection time but also improves safety because bridge inspection sites are fraught with hazards.The brief inspection system comprises the 10-screen sequence shown in Fig. 7. The inspector proceeds with the inspection in accordance with the inspection items displayed on the screen. The screen in Fig. 7(a) shows a list of bridges recorded in the system, from which the inspector chooses the bridge to be inspected. The list is displayed in order of proximity to the current location of the client device, reducing the need to scroll through a long list to find the appropriate bridge; the top bridge shown in the list is usually selected. The screen in Fig. 7(b) shows the previous inspection record for the selected bridge. After tapping the New Inspection button shown in Fig. 7(b), the inspector may start the bridge inspection. If the previous inspection record needs to be checked/reviewed before starting a new inspection, the Show Inspection Sheet button can be tapped. The screen in Fig. 7(c) is used to provide a safety check before starting the bridge inspection. The inspector should accordingly check their gear, then tap Yes, and the button Start Inspection will be automatically on.The screen in Fig. 7(d) is used to select the bridge element being inspected. The bridge elements are categorized into the five elements summarized in Table 3; the inspector may start the inspection from any element as convenient. The screens in Figs. 7(e–g) are used to input the inspection data. If no damage is found for the chosen element, No damage is tapped on the screen in Fig. 7(e); the inspection of that bridge element is now completed. However, if damage is found, Damaged is tapped and the various types of damage to the identified bridge element are shown on the screen in Fig. 7(f), as listed under the Inspection Item column in Table 3.Next, the screen for taking photos is displayed. On the screen shown in Fig. 7(g), six photos can be recorded for each element. The option Not Visible is provided for elements other than the road surface. If inspection of the superstructure, abutment, pier, and around bearings is not possible due to topography or other access difficulties, Not Visible can be selected. Furthermore, this option provides useful information that helps future inspectors consider their access and inspection methods by referencing photos in the inventory data, satellite photos on the internet, and so on in advance. This sequence of screen transitions, i.e., (1) identifying the existence of damage, (2) checking the damage type, and (3) taking photos of the damage, remains the same regardless of which element the inspector selects on the screen in Fig. 7(d). After taking the photos, the user is returned to the screen to select another bridge element, as shown in Fig. 7(h).After the completion of each element inspection, the color of the button showing that bridge element is changed to light blue. The inspector can then continue to inspect other elements of the bridge. When the inspection is completed for all elements, the button Comment by Inspector is made available [Fig. 7(i)], and the inspector can then add their comments, signature, and name [Fig. 7(j)]. The inspection result is subsequently stored on the iPhone, and the results for each bridge can be output as an inspection report, as shown in Fig. 8. The aforementioned bridge inspection procedural flow uses the brief inspection system developed by the authors.Evaluation of Damage DegreeThe bridge inspection method applied in the proposed system involves checking for the existence of the damage items listed in Table 3; if any damage is found, a photo of the damage scenario is captured and recorded. Each damage item is then assigned a score between 1 and 10, as indicated in Table 3. Minor damage is assigned a low score, whereas major damage (such as the settlement of the substructure) is assigned a high score. These assigned points are set as an initial value based on author experience as a professional engineer specializing in structural and material. The points for the damage items are then summed to obtain the total score for each corresponding member. These scores are then evaluated in terms of three damage levels (DLs) based on the judgment criteria determined for each member type (DLs I–III in Table 3); for each member, one point is given for DL I, three points for DL II, and five points for DL III. Weights of 10%, 30%, 10%, 20%, 20%, and 10% are then allocated to the road surface, superstructure, deck slab, abutment, pier, and around bearing member types, respectively. In the case of single span, the abutment accounts for 40% as the sole substructure. The sum of the values obtained by multiplying the score for each member (A) by the weight for the corresponding member type (B) is then used as the damage score for the entire bridge (T), as follows: (1) The damage degree of the entire bridge is divided into four levels according to the value of T, as indicated in Table 4. Thus, the system can evaluate bridge damage at multiple levels, such as the existence of damage to a member, level of damage to a member, and level of damage to an entire bridge. This makes it possible to search for the following in a database: •bridges with cracks in concrete girders,•bridges with severe damage to the superstructure and/or substructure, and•bridges that require urgent countermeasures.Table 4. Division of damage degree for a whole bridgeTable 4. Division of damage degree for a whole bridgeDamage degreeValue of TSD (serious damage)Above 1.5D (damage)1.0 to 1.5O (observation required)0.6 to 0.9N (no damage)Under 0.6Moreover, the score allocated to each damage item, classification criteria of damage levels, score per member, and/or weight for each member type summarized in Table 3, as well as the classification criteria presented in Table 4, can be adjusted based on the collected data and photos in accordance with the administrator’s policy for bridge maintenance; for example, more emphasis could be placed on damage to the superstructure and/or deck slab.Practical Results of the Proposed SystemThe authors introduced the proposed system for the baseline survey in the Project for Capacity Development for Road and Bridge Maintenance in Madagascar from the end of June to the beginning of July 2021, which gathered data describing 125 bridges (Table 5).Table 5. Number of bridge data collected per dayTable 5. Number of bridge data collected per dayDateBridges23 June724 June1425 June1026 JuneNo survey27 June428 June729 June1230 June81 July122 July63 July114 July105 July166 July8Total125Average9.6To conduct the survey, the system operation was explained online and the data from several bridges were gathered on a trial basis because the authors could not directly visit Madagascar owing to the global COVID-19 pandemic. After the authors confirmed that the trial data were satisfactory, the survey was conducted by local staff (a consulting company) in Madagascar starting June 23, 2021.Although the quantity of bridges inspected varied in the range of 4–16 per survey day, this was probably due to the distance between bridges and the road conditions during travel. The average data collection rate was 9.6  bridges/day, which is close to that at the beginning of the study conducted by Watanabe et al. (2021) in Cambodia (10.0  bridges/day). However, unlike the survey conducted in Cambodia, instructions for using the system were provided online and the bridge data were gathered by remotely managing local staff from Japan; yet the fact that the same data collection rate was obtained suggests that the system was easy to operate and simple to handle, even for first-time users.Iwamasa et al. (2022) conducted a bridge survey in Tajikistan around the same time using the same method employed by Watanabe et al. (2021) in Cambodia under the same remote instruction conditions as the Madagascar bridge survey owing to the COVID-19 pandemic. Unfortunately, a direct comparison cannot be made under completely identical conditions because of the different topographic and climatic conditions in Madagascar and Tajikistan. However, the system and devices used and the fact that the inspectors were operating the system for the first time were identical; therefore, a partial comparison is possible to determine the effects of the system improvements applied in the Madagascar bridge survey. In the Tajikistan bridge survey, data from a total of 431 bridges were collected over a total of 55 days using a maximum of two teams/day; thus, an average data collection rate of 5.7 bridges/day/team was achieved.The bridge inspection system implemented by Watanabe et al. (2021) in Cambodia required inspections to be conducted in a predetermined order [road surface, superstructure (main girders and deck slab), around bearing, and substructure (abutments and piers)]. Therefore, if damage to the deck slab was found during the inspection of the bridge pier, it was necessary to return all the way to the screen for inspecting the deck slab; this required additional recording time. The system introduced in this paper overcame this limitation by allowing the user to return to the relevant part of the bridge with just a few taps, thus making it possible to efficiently record inspections. As a result, the average data collection rate during the Madagascar bridge survey using the proposed system was approximately 1.7 times higher than that in during the Tajikistan bridge survey performed by Iwamasa et al. (2022), suggesting that the new method of selecting the bridge element to be inspected, shown in Fig. 7(f), was effective.In terms of damage evaluation, which is the most important aspect of the bridge inspection system, examples of damage photographs of bridges assessed to have serious damage (SD) based on the criteria in Tables 3 and 4 are shown in Fig. 9. Clearly, bridge administrators can use this system to quickly identify bridges classified as SD in the database and consider countermeasures.Although some of the photos shown in Fig. 9 for bridges determined to exhibit SD only depict minor damage, the points assigned for each DL in Table 3 are initial values; the points for each inspection item and criteria defining the DLs can be reviewed based on the obtained inspection results, and the accuracy can be improved. These tasks are part of the bridge maintenance and management cycle, which can be completed with the support of the proposed system.ConclusionsThe authors developed a system to collect bridge data using smartphones and implemented it in Madagascar to address the lack of bridge data for formulating bridge maintenance plans in developing countries where bridge maintenance management will be tackled in the future. The following points were considered to ensure that the system can be operated easily in developing countries by those working on bridge maintenance management: •A selective input method (pull-down system) was used for items with limited inputs such as region name and material type to prevent incorrect input and differences in notation among inspectors.•Unentered items were highlighted with a red background to prevent omissions.•On the input screen, the keyboard was displayed for text input and the numeric keypad was displayed for numeric input to ensure smooth input.•A link to another map application ( was provided to check the accuracy of the automatically acquired location information in the field.The proposed system was able to collect data on approximately 10 bridges per day during a project in Madagascar. For bridges that were classified as having serious damage (SD) according to the scores allocated to each inspection item in Tables 3 and 4, the damage level judgment criteria were extracted, and damage photos were confirmed as shown in Fig. 9. Most of this damage was classified as SD, indicating that the system is useful for identifying bridges that require countermeasures based on inspection records. However, some bridges were classified as SD but did not require immediate countermeasures because the points assigned to each DL in Table 3 are based on safety criteria. In a second round of inspections, the proposed system can be made more efficient and effective by reviewing the score distribution based on the results of the first inspection, and the operation of the system can be improved.The authors could not travel to Madagascar owing to the COVID-19 pandemic; therefore, the operation of the system was explained online, verifying that the proposed system can be used by local engineers who lack sufficient experience in bridge inspection. In terms of accuracy, the inspection results are based on the observed existence of damage. Although the DL of each bridge element was not evaluated to determine the accuracy of these observations, the use of standardized damage items and scores was generally sufficient to identify which bridges require countermeasures.In developed countries such as the US and Japan, many studies have been conducted that utilize existing bridge data such as bridge inventories and inspection records at a high level to realize efficient bridge maintenance and management; however, many developing countries do not have such data. The proposed bridge database system was therefore developed to facilitate the recording of bridge inventory and inspection data considering the actual conditions and issues common in developing countries such as poor connectivity, inconsistent data, a lack of experience in bridge inspections and other maintenance and management work, a shortage of bridge engineers, and so on. The authors believe this system can accordingly serve as a cornerstone for the development of future bridge maintenance and management technology in developing countries.Because the proposed system is intended to facilitate the efficient collection of basic bridge data, it is not currently capable of predicting deterioration or any other advanced functionalities currently being studied in developed countries. However, because the system includes bridge condition assessments and damage photographs that allow complete bridge inspection data to be recorded in chronological order, we believe that it establishes a foundation for the future development of a bridge database system capable of predicting deterioration.ProspectsTechnology related to the maintenance and management of road structures, which includes bridges and tunnels, will be further investigated in the future. The authors understand that there are many countries that want to prepare maintenance management plans for road structures but do not have the necessary basic inventory data required for planning. The developed system will be very useful in such countries. The authors would therefore like to globally deploy the system to countries without bridge databases. Therefore, the system desires to be compatible with iOS and other operating systems (OS) such as Android and Windows, which will be one of the future challenges.Data Availability StatementSome or all data, models, or code that support the findings of this study are available from the corresponding author upon reasonable request. The item list contains (1) bridge inventory data; and (2) bridge inspection data. However, some or all data, models, or code generated or used during the study are proprietary or confidential in nature and may only be provided with restrictions. The item list contains (1) bridge location data; and (2) application program.AcknowledgmentsWe would like to thank Editage for English language editing.References Alogdianakis, F., D. C. Charmpis, and I. Balafas. 2020. “Using data analysis to extract structural deterioration information from the US national bridge inventory database.” In Proc., RILEM Spring Convention and Conf., 265–277. Cham, Switzerland: Springer. Anwar, S. A. 2010. Bridge performance measures (BPM). Detroit, MI: USDOT, Federal Highway Administration. Henry, M., C. Yamasaki, K. Nagai, K. Matsumoto, and H. Yokota. 2018. “Technology transfer for safe and sustainable road bridge life cycle management in Myanmar.” J. Disaster Res. 13 (1): 88–98. Ibayashi, K., O. Youda, Y. Tanaka, and K. Maruyama. 2013. “Road bridge brief inspection and input system with tablet computer.” In Proc., Third Int. Conf. on Sustainable Construction Materials and Technologies. Coventry, UK: Coventry Univ. Iwamasa, H., E. Katayama, T. 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