Frequency Of Accidents Research Articles

URBAN TRAFFIC CRASH ANALYSIS USING DEEP LEARNING TECHNIQUES

Road accidents are concerningly increasing in Andhra Pradesh. In 2021, Andhra Pradesh experienced a 20 percent upsurge in road accidents. The state's unfortunate position of being ranked eighth in terms of fatalities, with 8,946 lives lost in 22,311 traffic accidents, underscores the urgent nature of the problem. The significant financial impact on the victims and their families stresses the necessity for effective actions to reduce road accidents. This study proposes a framework that collects accident data from regions, namely Patamata, Penamaluru, Mylavaram, Krishnalanka, Ibrahimpatnam, and Gandhinagar in Vijayawada (India) from 2019 to 2021. The dataset comprises over 12,000 records of accident data. Deep learning techniques are applied to classify the severity of road accidents into Fatal, Grievous, and Severe Injuries. The classification procedure leverages advanced neural network models, including the Multilayer Perceptron, Long-Short Term Memory, Recurrent Neural Network, and Gated Recurrent Unit. These models are trained on the collected data to accurately predict the severity of road accidents. The project study to make important contributions for suggesting proactive measures and policies to reduce the severity and frequency of road accidents in Andhra Pradesh.

Risk analysis of inland waterways transportation on the Niger Delta Basin, Nigeria

This study aimed at analyzing accidents and risk on inland waterways transport operations in the Niger delta basin, Nigeria. Quantitative data obtained from the dada base of the National Inland waterways Authority (NIWA) were subjected to risk assessment methods. The results reveal an estimated average individual risk (AIR) value of 6.2x10-5, a fatal accident rate (FAR) of 975 fatalities per 8640 exposed hours; and accident frequency rate (AFR) value of 0.7% for the inland waterways of Niger delta. It concludes that waterways of Niger delta have high risk indices and potentials of accident occurrence due to poor maintenance dredging, enforcement of regulations; and thus recommends that NIWA should invest optimally in safety awareness and policy enforcement for sustainable waterways operations in Nigeria.

Exploring traffic accidents patterns: Spatial distribution and socio-economic determinants

<p class="Els-keywords">This study employs a machine learning methodology, specifically the decision tree algorithm, in conjunction with the Quantum Geographic Information System (QGIS), to conduct a rigorous analysis of traffic accident data. The research aims to investigate various factors associated with traffic accidents, with a particular emphasis on their spatial distribution and the socio-economic determinants contributing to recurring accidents caused by drivers. The study focuses on the city of Duhok, located in the Kurdistan Region of Iraq, and utilizes a questionnaire to collect data from drivers regarding accident locations and the frequency of accidents within the past decade (from 2010 to 2020). The findings of the study reveal that the city center experiences the highest concentration of accidents, while severe collisions tend to occur in specific “black spots” scattered across the city’s road network. The decision tree model, employed to classify drivers with multiple accidents, identifies the primary causes of accidents as traffic conditions, traffic law violations, and overspeeding. Furthermore, the accident locations are found to be influenced by various factors, including different types of road hierarchy. The age and gender of drivers also contribute to accident patterns. These research findings have practical implications for enhancing road safety measures and reducing the frequency of traffic accidents. The utilization of machine learning techniques, combined with the analysis of spatial data through QGIS, provides a comprehensive understanding of the underlying factors contributing to accidents. Moreover, this research contributes novel insights to the field of road traffic accidents and safety, particularly in the context of the city of Duhok in Kurdistan Region, Iraq, and provides a valuable reference for future studies in the domain of road safety and urban planning.</p>

Non-Fatal Agricultural Injuries and First Aid Self-Efficacy Among Greenhouse Workers in Turkey

ABSTRACT Objective This study aimed to see if there was a link between first aid self-efficacy and the frequency of occupational accidents and non-fatal agricultural injuries in greenhouse agriculture workers. Methods This cross-sectional study was conducted with 251 people in a district center. Sociodemographic, occupational accident, and injury questionnaires prepared by the researchers and the First Aid Self-Efficacy Scale were used to collect the data. SPSS 25.0 software was used to evaluate the data and descriptive statistics; the Mann-Whitney U test and Kruskal Wallis analysis of variance were applied in the analysis. Results 71.4% of the participants experienced an occupational accident by falling and slipping; 41.7% were slightly injured after the accident, and 63.2% experienced injuries in fractures, sprains, and crushes. We found that most injuries were in the lower extremities (33.2%), and 66.4% were admitted to the hospital. We ascertained that male workers’ median first-aid self-efficacy scores were significantly higher than those of female workers (p < .05). We determined there was no significant difference between first-aid self-efficacy scores according to other sociodemographic variables, occupational accidents, or injury data (p > .05). Conclusion Occupational accidents and non-fatal agricultural injuries are common in greenhouse agriculture, and male workers have higher first-aid self-efficacy than female workers. Since greenhouse work is a hazardous line of work, providing simple medical first-aid training would be useful for those working in this field.

Is the analysis of territorial compatibility in the vicinity of road hazmat transport routes a necessity for developing countries? A case study of Romania

The way dangerous goods are transported on roads within the European Union is regulated by international agreements that have been transposed into national legislation. Unlike European policies that focus on preventing major accidents involving dangerous substances in the industry, the component of territorial planning in areas exposed to technological hazards is not given similar attention when it comes to transport routes of dangerous goods. Since both the transport of hazardous materials and the activities of large industrial operators involve the handling of the same types of dangerous substances, they share similar associated hazards. Within this framework, a question arises as to whether decision-makers should accord greater consideration to the land use policies in the areas adjacent to transportation routes. In this study, the case of Romania was analyzed in detail, with the objective to firstly identify some particularities in how the primary road infrastructure is developed in relation to other European countries. Since the territorial compatibility near large industrial operators is established based on specific regulations at the national level, but there is no similar regulation for the transport of dangerous substances, another objective was to adapt and implement a methodology for the analysis of the territorial compatibility in the proximity of the national roads network. The proposed methodology utilizes open-source data and Geographic Information Systems (GIS) for analysis. It also involves the extensive application of existing rules on territorial compatibility for technological risks, specifically in the context of hazmat transport. The results of this study indicate that the primary road transport network in Romania has different characteristics compared to that of other countries, which determines a higher level of exposure to the hazards specific to the road transport of hazardous materials. Additionally, from an analysis of gasoline and diesel transport on national roads and the implementation of a territorial compatibility matrix, we observed instances of territorial incompatibility in the current state, particularly in areas close to the road, especially for scenarios with a relatively high accident frequency. Thus, the way future large road infrastructure development projects address risks related to dangerous goods transportation and the implementation of environmentally conscious land management strategies can contribute to society's sustainable development.

The Correlation Of Unsafe Action And Unsafe Condition On Work Accident Among Nurses At Dr Tadjuddin Chalid Hospital Makassar

Nurses working in hospital settings face a heightened susceptibility to work-related accidents, which primarily stem from two underlying factors: unsafe behaviour and hazardous conditions. Work accident data at Dr Tadjuddin Chalid, there are 12 reported cases of work accidents in 2021. The objective of this study was to establish the correlation between unsafe actions, unsafe conditions, and the frequency of work accidents among nurses at Dr Tadjuddin Chalid Makassar Hospital. The research methodology employed for this investigation was observational, adopting a cross-sectional approach. The targeted population encompassed 205 individuals, with a final sample size of 136 nurses being involved in this research endeavour. The sample is taken using a simple random sampling method. Respondent data collection using a questionnaire. Data analysis used the chi-square test to see the relationship between independent variables, namely unsafe actions (perceptions, work experience, work stress, work shifts and supervision) and unsafe conditions (work environment, tools/materials and dangerous unsafe environment) with the occurrence of work accidents. The findings indicated a notable correlation between unsafe behaviour and work accidents (p-value = 0.001), alongside a significant relationship between unsafe conditions and work accidents (p-value = 0.007). In summation, it can be concluded that both unsafe behaviour and unsafe conditions are connected to the incidence of work accidents at Dr. Tadjuddin Chalid Makassar Hospital. It is recommended that the hospital emphasizes enhancing the work environment's conditions and elevating the quality of training and supervision. These measures are essential for mitigating the prevalence of work accidents among nurses.

A Control System Using Speech Recognition AMR in Robotic System

Voice command is currently a vital task for developing smart assistive devices, especially since the frequency of accidents continues to climb, posing a huge shift in handicapped people’s lifestyles which makes producing a material to support them in their daily lives a significant challenge. One of the proposed options is to add an embedded system with a machine learning algorithm represented by voice recognition to assist handicapped people. In this paper, we have implemented a voice command control system in Arabic through an AMR Voice application in Smartphone with a microcontroller demonstrates a sophisticated integration of hardware and software technologies. The utilization of Bluetooth technology which acts as a communication channel with the LED light circuit , which will then be connected to the Arduino to create a system based on voice commands.

Principles of formulating measures regarding preventing coal and gas outbursts in deep mining: Based on stress distribution and failure characteristics

As the increasing demand for coal and the depletion of shallow coal resources, the tendency of coal mining in China is progressively shifting to deeper areas, which brings about a circumstance where the frequency and intensity of coal and gas outburst accidents have further deteriorated. Nowadays, there are many outburst prevention measures being applied on site, while this disaster still occurs from time to time. Therefore, to better improve the preventing outcome of them, this paper came forward with some principles, based on the mechanical theory of deep mining and damage evolution procedure concerning coal containing gas underneath the impact load. The primary conclusions were as follows: the stresses, strains, and associated widths in the three areas, namely fracture area, plastic area, and elastic area, in front of the working face were recalculated by considering stress-softening and dilatancy of coal mass. The damage evolution of gas-bearing coal mass under impact loading was displayed in the LS-DYNA numerical simulation as a process of compaction followed by destruction. The proposed principles could be split into two perspectives, one for the fracture area, specifically, to minimize the descending of the coal mass’s strength in this area; another for the stress-concentration zone, namely, to abate the thrust due to extrusion and deformation, on the coal body which was located in the front area. According to those principles, a preliminary goal-reaching parameter was proposed and it was implemented for the evaluation of advanced drilling. The results will cooperate to rationalize the design and layout of local outburst prevention measures, thereby enhancing the efficiency of control and ameliorating the deteriorating scenario of outburst disasters.

Analysis of Building Construction Jobsite Accident Scenarios Based on Big Data Association Analysis

Analysis of Building Construction Jobsite Accident Scenarios Based on Big Data Association Analysis

Risk Assessment of Sudden Water Pollution Accidents Associated with Dangerous Goods Transportation on the Cross-Tributary Bridges of Baiyangdian Lake

The issue of sudden water pollution resulting from accidents is a challenging environmental problem to address. The frequency of transport accidents involving hazardous materials over tributary bridges is steadily rising due to rapid industrialization and urbanization processes. This trend poses a significant threat to both the water’s ecological environment and human well-being. To effectively mitigate the risks associated with water pollution caused by accidents during the transportation of dangerous goods, this research focused on Baiyangdian Lake, the largest freshwater lake in North China. Thid study employed the expert judgment fuzzy language method and Bayesian network model as analytical tools to assess and analyze the potential risks associated with sudden water pollution accidents caused by the transportation of hazardous materials on bridges spanning tributaries. Through an examination of the various risk factors involved, the research identified four primary indicators and ten secondary indicators. Additionally, an oil leakage accident scenario was simulated, and recommendations for risk prevention and control measures were provided. The findings of the study indicated that: (1) The likelihood of risk associated with driver factors, vehicle emergency factors, fuel tank emergency factors, road factors, and lighting factors is elevated. (2) The probability of a dangerous goods transportation accident occurring on the Baiyangdian cross-tributary bridge is substantial, thereby presenting a potential hazard to both the water environment and human health. (3) Vehicle emergency factors, vehicle wear factors, and weather factors exert a significant influence on the incidence of accidents. (4) The highest likelihood of accidents is associated with a combination of factors, including driver fatigue, vehicle and fuel tank deterioration, and adverse weather conditions. (5) In instances where the vehicle and fuel tank are well-maintained, the probability of accidents is greatest on the cross tributary bridge, particularly when the driver is fatigued, weather conditions are unfavorable, and there is a lack of street lighting during nighttime. Implementing emergency prevention and control measures proved to be an effective approach in mitigating the risk of sudden water pollution accidents. This study offers valuable insights into risk mitigation and management strategies for emergent water pollution incidents, and the framework presented herein can be readily applied to other rivers worldwide confronting comparable risk challenges.

Construction accident data mining: A retrospective study using structural equation modeling based on 10-year data.

The data mining of construction accidents based on a robust modeling process can be used as a practical technique for reducing the frequency of construction accidents. This study was designed to data-mine construction accidents. This study was conducted in 2020 on construction accidents in Iran for ten years (2009-2018). The instruments to collect the required data were the checklists and descriptive reports of the accidents. The dependent variables of the study included reactive safety indicators related to construction accidents (lost working days (LWD) and total accident costs (TAC)). The independent variables consisted of four latent factors: personal variables, organizational variables, unsafe working conditions, and unsafe acts. The data were collected based on the conceptual model designed for data mining. The data mining process was carried out based on the structural equation modeling by IBM AMOS V. 23.0. A total of 5742 construction accidents occurring in 10 years were analyzed. The means of TAC and LWD indicators were estimated to be 248.20±52.60 days and 1893.10±152.22 $. These two indicators directly correlated with the two latent factors of unsafe conditions and unsafe acts and their related variables and were indirectly influenced by latent personal and organizational factors. The relationship between unsafe conditions and unsafe acts was significantly positive. The relationship between latent personal and organizational factors and the two construction accident indicators was significantly negative (p <0.05). The model results showed that personal and organizational variables could, directly and indirectly, affect reactive safety indicators in construction projects. Thus, these findings can be used to design and improve safety strategies to prevent and decrease construction accidents and incidents.

The Influence of Co-Worker Social Support and Job Satisfaction on Job Stress among Mechanics and Engineers in the Aviation Industry

The aviation industry is a field of work that requires high precision and concentration, leading to a high level of job stress. One prominent issue in aviation is the increasing frequency of incidents and accidents. This study aims to examine the influence of co-worker social support and job satisfaction on job stress among mechanics and engineers. The sample consists of 100 individuals working as mechanics and engineers in the aviation industry. Multiple linear regression analysis using Pearson correlation is employed for data analysis. The results indicate that co-worker social support and job satisfaction jointly account for 49.2% of job stress. Overall, the participants' co-worker social support and job satisfaction are moderate, while job stress is significantly high. The study shows that co-worker social support has a greater impact on job stress compared to job satisfaction. Keywords: co-worker social support, job satisfaction, job stress, mechanics, engineers.

Study on the leakage and diffusion behavior of hydrogen-blended natural gas in utility tunnels

Incorporating the hydrogen-blended natural gas pipeline into utility tunnels increases the potential safety risk caused by gas leakage and diffusion. In this paper, a numerical model for the leakage and diffusion of hydrogen-blended natural gas in the tunnel was established to study the influences of ventilation mode, initial pipeline pressure, hydrogen blend ratio (HBR), and leak size on gas leakage and diffusion. The results indicate that gas accumulates at the tunnel's top under natural ventilation. When the HBR exceeds 20%, the safety risk in the tunnel increases significantly. Unlike natural ventilation, mechanical ventilation significantly reduces the high-concentration area's impact range. Under the dynamic adjustment of ventilation frequency, the leak size significantly impacts gas diffusion concentration, while the HBR has the slightest impact. When the HBR is no higher than 40%, the pipeline pressure is no higher than 0.4 MPa, and the leak size is no high than 5 mm, the accident ventilation frequency of 12 times/h could ensure the leaked gas concentration is lower than the alarm concentration. A leaked gas concentration prediction model was established to provide a basis for predicting the distribution of the leaked gas concentration in actual engineering.

Safe Path Prediction Using Machine Learning

Abstract: Due to the exponential increase in traffic nowadays, the incidence of accidents also increases proportionally. With the rapid increase in accidents, the ability to predict and predict the best path to an accident is very important not only for the transport department to make scientific decisions, but also for individuals to know less paths to accidents to travel the safest way. According to the current scenarios, it would be good to analyze the correct path with less accidents. In this, we studied the interrelationship between accidents, road conditions, weather conditions and predicted a safe and less frequent accident occurrence path among all the paths that can be taken from the source to the destination. We built using machine learning algorithms like Support Vector Machines and Logistic Regression. The main topic is to design the safest route of all the routes based on the accident rate. Conditions such as weather conditions, road conditions, lighting conditions, vehicle type, etc. By inputting these conditions into a machine learning model for a specific location, one can predict the frequency of accidents that will occur at a specific location, whether the location is safe. Based on the safety of individual locations, user can concludes the safety of the path

Multi-sensor data fusion and bidirectional-temporal attention convolutional network for remaining useful life prediction of rolling bearing

Abstract Remaining useful life (RUL) prediction is crucial in the field of engineering, which can reduce the frequency of accidents and the maintenance cost of machinery. With the increasing complexity of rotating machinery, the data analysis methods based on deep learning have become the mainstream methods of prediction work. However, most of the current RUL prediction methods only use single-sensor data as input, which cannot effectively use multi-sensor data. In addition, as an advanced deep learning prediction method, temporal convolutional network (TCN) only uses the past time information of vibration data to determine the current health status of bearings, while ignoring the importance of future time information of vibration data. To solve the above problems, a bearing RUL prediction method based on multi-sensor data fusion and bidirectional-temporal attention convolutional network (Bi-TACN) is proposed in this paper. In multi-sensor data fusion, multi-sensor data are combined into multi-channel data, and a channel-weighted attention is designed to emphasize the importance of each sensor data. Compared with traditional multi-sensor data fusion, the proposed fusion method allows deep prediction networks to learn more useful feature information from multi-sensor data. Then, Bi-TACN is developed to predict the RUL of bearings. Bi-TACN is mainly composed of the forward TCN block and the backward TCN block, both of which can learn the past and future time information of multi-sensor data simultaneously. Moreover, a temporal attention mechanism is embedded in Bi-TACN to adaptively calibrate the weights of the two TCN blocks, so as to achieve dynamic feature fusion of past and future time information. RUL prediction experiments are carried out through Xi’an Jiao tong University bearing dataset and PHM 2012 bearing dataset respectively. Compared with the advanced prediction methods, the proposed method can accurately predict the RUL of more types of bearings and has low prediction errors.

ANALISIS KINERJA KESELAMATAN DAN KESEHATAN KERJA (K3) PADA PROSES PRODUKSI SAUS DENGAN METODE FAULT TREE ANALYSIS

The production process for making sauces requires a performance appraisal so that the results are effective and efficient. In production, performance problems sometimes occur, such as low productivity and accidents. The relationship between employee performance, such as work safety greatly affects work productivity. The purpose of this study was to analyze the performance of K3 which includes the Frequency Rate (FR), Severity Rate (SR), and T-Safety Value (NTS) so that it will produce how big the relationship is between the accident rate and work productivity. This study uses the Fault Tree Analysis (FTA) method where to build an FTA flowchart, it is necessary to identify work accident data, build a safety tree, measure work productivity, and draw conclusions. This research has produced several analyzes using FTA where the FR, SR, and NTS levels can already be known. The results of measuring the FR value show a decrease in the frequency of disability injuries and the severity of work accidents from year to year, there is a decrease from year to year. This research has also succeeded in increasing employee work productivity due to the low value of the FR and SR levels each year. If linked to NTS, every year the relationship between work safety and productivity will improve. So from the results of this analysis, there is a relationship between the frequency of work accidents and the level of work productivity that occurs in the production process.

Causes, Types and Management of Fracture of Dentate Region of Mandible

Aim: The mandible fracture ranks as the second most often occurring facial fracture. The advent of high-speed automobiles has led to a significant increase in the frequency of accidents in recent times. Mandibular fractures are observed as a notable occurrence of maxillofacial trauma in the region of Multan. Purpose: To determine the Causes, types and management of fracture of dentate region of mandible fracture. Method: The present research is an observational and descriptive investigation including a sample of 52 patients diagnosed with mandible fractures. The study was done at the Nishter Institute of Dentistry in Multan, Pakistan, spanning from September 2021 to February 2023. Following the endorsement of the research by the Ethical Review Board of the hospital, patients were recruited using a non-probability sequential sampling method. This research included patients who had a history of trauma and were admitted to Nishter Institute of Dentistry in Multan, Pakistan, as well as those from the surrounding districts of Multan. The assessment of mandibular fractures included doing extra-oral and intra-oral clinical evaluations, as well as obtaining panoramic and posterior-anterior radiographs of the mandible to establish a diagnosis. The data collected was then subjected to statistical analysis. Result: Among the sample of 52 individuals diagnosed with mandibular fractures, the age group of 21-30 years had the greatest proportion, with a notable male preponderance. The leading causes of fractures were road traffic accidents and assault, with the parasymphysis being the most often affected anatomical region. The occurrence and aetiology of mandibular fracture are indicative of the prevailing trauma patterns in a given population and may serve as a valuable resource for informing the development of initiatives aimed at mitigating and managing such injuries. Conclusions: Patients in the older age (51 years and over) exhibited a higher prevalence of fracture sites in comparison to patients in the younger age. This observation might perhaps be ascribed to the presence of a larger tooth-to-bone ratio. As a result, a decrease in bone density was seen among participants in the younger age category, whereas those in the older age category exhibited an elevation in bone frailty Keywords: Dentate fracture, mandible, trauma

Features of coronary pathology and its relationship with myocardial fibrosis markers in patients with resistant hypertension

Aim. To evaluate the severity of coronary atherosclerosis and its association with biochemical markers of fibrosis in patients with coronary artery disease (CAD) and resistant hypertension (RHT).Material and methods. The study included 39 patients with CAD and RHT. All patients underwent 24-hour blood pressure (BP) monitoring, office BP numbers were measured. Laboratory diagnostics included routine tests, as well as determination of serum lipocalin, plasma concentration of matrix metalloproteinases 2 and 9 (­MMP-2, MMP-9), tissue inhibitor of matrix metalloproteinases-1 (TIMP 1). Coronary atherosclerosis in patients was assessed retrospectively according to medical records with an assessment of the protocols of invasive coronary angiography and multislice computed tomography, performed no more than a year ago from the moment of inclusion in the study with no clinical signs of CAD progression. Obstructive atherosclerosis was considered a coronary artery narrowing by more than 50%.Results. Considering the results of previous coronary angiography, the patients were divided into two groups. In the first group (n=20), coronary artery stenosis was &lt;50%, in the second (n=19) &gt;50% (p&lt;0,05). The compared groups of patients were comparable in sex, age, duration of hypertension, blood pressure level, and the number of antihypertensive drugs taken. There were no differences in blood lipid profile, basal glycemia, uric acid levels, and the frequency of previous cerebral accidents. However, the incidence of diabetes in group 2 was significantly higher (p&lt;0,05). Additionally, there was a significant difference in serum levels of lipocalin and MMP-2 with higher values of these indicators in patients with coronary atherosclerosis stenosis (p=0,02).Conclusion. In patients with RHT with symptoms and signs of myocardial ische­­mia, the incidence of obstructive coronary atherosclerosis according to coronary angiography is 50%. Diabetes in this category of patients indicates a more frequent obstruction of coronary bed. An increase in the level of MMP-2 and lipocalin in this category of patients is associated with more severe coronary damage and can be considered as an indirect indicator of obstructive coronary atherosclerosis.

COVİD-19 Enfeksiyonunun İkinci Dalgasında Çocuklarda Ev Kazaları: Tek Merkez Deneyimi

Objective: The COVID-19 pandemic has affected the whole world in terms of health, social life, and economics. In this study, the frequency of pediatric home accidents in the second wave of the pandemic, where social isolation continues, was investigated. Material and Methods: This is a single center, retrospective study. We evaluated cases of patients under the age of 18 who were admitted to the hospital due to a home accident between November 1, 2020 and January 31, 2021 (the second wave of the pandemic). Results were compared with the patients who were admitted to the same emergency department within the same period of the previous year. Researchers examined home accidents in three groups: crash-fall-incision (1), intoxication-foreign body ingestion (2), and burns (3). The patients were divided into four age groups: 0-1 year, 2-5 years, 6-11 years, and 12-17 years. Results: The study was completed with 607 cases pre-Covid and 683 cases post-Covid. The median age was 44.4 month (17-57) from 2019-2020 and 49.1 month (18-64) from 2020-2021 (p=0.154). The outpatient and sequela-free discharges were more frequent in both periods (p=0.046). In the second wave of the pandemic, there was an increase in burns and fall related admissions compared to before the pandemic (p&amp;lt;0.001). All types of home accidents were frequently detected at the ages of five years and younger. Conclusion: In this study, analyzing the second wave of the pandemic compared to pre-pandemic times, Researchers noted a decrease in the number of emergency admissions and an increase in admissions related to home accidents.

Locomotive engineer safety with single manning operation

ABSTRACT The paper is about practice, rather than research, and shows how a complex systems engineering project was done. The project was unique, involving a problem never before investigated, namely, to find the difference in occupational safety of a train driver between being alone in a locomotive cab and having an accompanying assistant. The project used a systems methodology discussed elsewhere. It required understanding the overall New Zealand Rail system and ensuring the objective was clear. A strategy was developed based on a set of system principles. Fault trees gave accident probabilities, from which relative values of Fatal Accident Frequency Rates were computed. As a practical simplification, detailed analysis was confined to a limited part of the overall rail system which could be taken as representative of the whole. Care was taken to treat input information as a whole rather than as separate unconnected items, emphasising information quality, which varied depending on type and source. Major points were the importance of (a) a clear and coherent strategy including careful system decomposition, (b) having a body of information of high and consistent quality, (c) fostering clarity and transparency in communication, and (d) having – and learning – good communication skills. This work is part of a Special Issue on Systems Perspectives: Clarity through Examples (see Dias 2023).