Safety Measures Research Articles

Bidirectional Long Short-Term Memory Development for Aircraft Trajectory Prediction Applications to the UAS-S4 Ehécatl

The rapid advancement of unmanned aerial systems in various civilian roles necessitates improved safety measures during their operation. A key aspect of enhancing safety is effective collision avoidance, which is based on conflict detection and is greatly aided by accurate trajectory prediction. This paper represents a novel data-driven trajectory prediction methodology based on applying the Long Short-Term Memory (LSTM) prediction algorithm to the UAS-S4 Ehécatl. An LSTM model was designed as the baseline and then developed into a Staked LSTM to better capture complex and hierarchical temporal trajectory patterns. Next, the Bidirectional LSTM was developed for a better understanding of the contextual trajectories from both its past and future data points, and to provide a more comprehensive temporal perspective that could enhance its accuracy. LSTM-based models were evaluated in terms of mean absolute percentage errors. The results reveal the superiority of the Bidirectional LSTM, as it could predict UAS-S4 trajectories more accurately than the Stacked LSTM. Moreover, the developed Bidirectional LSTM was compared with other state-of-the-art deep neural networks aimed at aircraft trajectory prediction. Promising results confirmed that Bidirectional LSTM exhibits the most stable MAPE across all prediction horizons.

Comparison of E-Scooter and Bike Users’ Behavior in Mixed Traffic

This study aims to investigate the different behaviors with respect to safety measures related to the interaction of e-scooters and bikes with cars in mixed traffic. E-scooters are relatively new vulnerable road users, and their behavior is still not fully understood. For this purpose, an observational study was carried out at an unsignalized at-grade intersection in the city of Catania, Italy. A total of 128 interactions between cars and e-scooters and 89 interactions between cars and bikes were detected. Specifically, two surrogate measures of safety were used, the time to collision (TTC) and post encroachment time (PET), which relate to the “crossing” and the “following” interactions between cars and bikes/e-scooters. The results show that 50% of the “crossings” involving bikes were close interactions with low TTCs representing high risk (TTC < 1.5); meanwhile, for the “crossing” interactions between cars and e-scooters, the same threshold of TTC relates to percentiles of more than 80%. In addition, more than 60% of interactions between cars and e-scooters were characterized by PET values representing a potentially high risk (PET < 1.0 s). The results provide a useful starting point for the elaboration and adaptation of new regulations for mixed traffic conditions including e-scooters that are currently being introduced in several countries with different rules. It should be noted that e-scooters are an intrinsically different transport mode from a bicycle, mainly because their interactions in mixed traffic show that they are prone to a higher risk of closer interactions.

Analyzing the Suitability of Vehicle Telematics Data as a Surrogate Safety Measure for Short-Term Crashes

Traffic safety analysis relies heavily on the comprehensiveness of traffic crash data. However, crash occurrences are rare events. Researchers have sought alternative measures closely linked to crash occurrences, known as surrogate safety measures, to address this challenge. The advent of vehicle telematics has introduced a valuable source of data, consisting of time-stamped positional information of vehicles, facilitated through telecommunication networks. Wejo Data Services Inc. collects vehicle telematics data through collaboration with various automotive original equipment manufacturers (OEMs) to furnish connected vehicle data along with driver event variables, such as braking and acceleration. This study seeks to investigate the relationship between hard-braking events and the incidence of total crashes and peak period crashes across different facility types using analysis of variance and negative binomial models. The results show a strong correlation between hard braking and crash frequency. The ratio of hard-braking events to crashes exhibits notable variations across peak hours, off-peak periods, and nighttime. Further, the coefficient of hard braking is significantly higher on freeways compared with non-freeways. The model performance of different short period models improved better than the extent of improvement in total crash model after hard braking was introduced as an explanatory variable. The marginal effects of hard braking on crash frequency on freeways are consistently higher than those in non-freeway segments.

Digital media in the economic empowerment of the Hijra community

Despite official recognition in 2013, the Hijra community in Bangladesh continues to endure persistent discrimination and exclusion, limiting them to traditional and menial professions and perpetuating their cycle of poverty and marginalization. This study examines the economic potential of digital media for the Hijra community and the barriers they face in harnessing it for economic empowerment. Through qualitative analysis conducted via semi-structured interviews with Hijra participants, we explore their perceptions of digital media’s opportunities and challenges. Thematic analysis reveals that while Hijras primarily use digital media for psychological needs, they recognize its potential for economic empowerment. However, they encounter barriers, such as financial constraints, limited education and digital literacy, and societal stigma, hindering their ability to leverage digital platforms for economic advancement. Drawing from our findings, we propose actionable recommendations, including policy changes, enhanced online safety measures, educational initiatives for digital literacy, public awareness campaigns, and financial assistance to enable the Hijra community to fully harness the economic potential of digital media and alleviate their socioeconomic struggles.

Sources of the Electromagnetic Pollution, Effects, Safety Measures

Sources of the Electromagnetic Pollution, Effects, Safety Measures

Inadequate food safety knowledge and hygiene practices among street food vendors in Dhaka, Bangladesh

Food safety remains a critical issue with outbreaks of foodborne illness. The knowledge gap of food safety and improper hygienic practices of food handlers are the key factors for the transmission of foodborne diseases. This study was conducted to investigate the level of food safety knowledge and practices among street food vendors in Dhaka City, Bangladesh, and its implications on consumers’ health. This cross-sectional study was conducted among 350 respondents in seven areas of Dhaka City. Trained data collectors gather data by interviewing street vendors using a pretested questionnaire. Most of the vendors (98%) were male, with 48% having secondary education and 85% having no food safety training. Although about 89% of the vendors were found to practice hand washing, only a small proportion of them practised using hand gloves while handling raw products (5.6%), cleaning tables (2.2%), preparing foods (1.3%) or handling garbage (0.9%). The education level of the vendors and their work experience were significantly correlated with their hand washing practice, wearing hand gloves and their knowledge about food-borne illnesses. The study demonstrated that formal education played a significant role in vendors’ knowledge and practice of health safety measures for food handlers to prevent foodborne illness. Effective food safety training and monitoring are needed to increase vendors' knowledge and practices, and in reducing foodborne diseases.

Low-Dose Buprenorphine Initiation for Hospitalized Patients With Chronic Pain and Opioid Use Disorder or Opioid Misuse: Protocol for an Open-Label, Parallel-Group, Effectiveness-Implementation Randomized Controlled Trial.

Buprenorphine is an effective medication for both opioid use disorder (OUD) and chronic pain (CP), but transitioning from full opioid agonists to buprenorphine, a partial opioid agonist, can be challenging. Preliminary studies suggest that low-dose buprenorphine initiation can overcome some challenges in starting treatment, but no randomized controlled trials have compared low-dose and standard buprenorphine initiation approaches regarding effectiveness and safety or examined implementation in hospital settings. In a pragmatic open-label hybrid type I effectiveness-implementation trial based in a single urban health system, 270 hospitalized patients with (a) CP and (b) OUD or opioid misuse are being randomized to buprenorphine treatment initiation using 5-day low-dose or standard initiation protocols. Outcomes include buprenorphine treatment uptake (primary), defined as receiving buprenorphine treatment 7 days after enrollment, and other OUD and pain outcomes at 1-, 3-, and 6-month follow-up (secondary). Data collection will also include safety measures, implementation of low-dose initiation protocols, patient acceptability, and cost-effectiveness. Comparing strategies in a randomized clinical trial will provide the most definitive data to date regarding the effectiveness and safety of low-dose buprenorphine initiation. The study will also provide important data on treating CP at a time that clinical guidelines are evolving to center buprenorphine as a preferred opioid for CP.

Ecological momentary assessment and cue-elicited drug craving as primary endpoints: study protocol for a randomized, double-blind, placebo-controlled clinical trial testing the efficacy of a GLP-1 receptor agonist in opioid use disorder

BackgroundDespite continuing advancements in treatments for opioid use disorder (OUD), continued high rates of relapse indicate the need for more effective approaches, including novel pharmacological interventions. Glucagon-like peptide 1 receptor agonists (GLP-1RA) provide a promising avenue as a non-opioid medication for the treatment of OUD. Whereas GLP-1RAs have shown promise as a treatment for alcohol and nicotine use disorders, to date, no controlled clinical trials have been conducted to determine if a GLP-1RA can reduce craving in individuals with OUD. The purpose of the current protocol was to evaluate the potential for a GLP-1RA, liraglutide, to safely and effectively reduce craving in an OUD population in residential treatment.MethodThis preliminary study was a randomized, double-blinded, placebo-controlled clinical trial designed to test the safety and efficacy of the GLP-1RA, liraglutide, in 40 participants in residential treatment for OUD. Along with taking a range of safety measures, efficacy for cue-induced craving was evaluated prior to (Day 1) and following (Day 19) treatment using a Visual Analogue Scale (VAS) in response to a cue reactivity task during functional near-infrared spectroscopy (fNIRS) and for craving. Efficacy of treatment for ambient craving was assessed using Ecological Momentary Assessment (EMA) prior to (Study Day 1), across (Study Days 2–19), and following (Study Days 20–21) residential treatment.DiscussionThis manuscript describes a protocol to collect clinical data on the safety and efficacy of a GLP-1RA, liraglutide, during residential treatment of persons with OUD, laying the groundwork for further evaluation in a larger, outpatient OUD population. Improved understanding of innovative, non-opioid based treatments for OUD will have the potential to inform community-based interventions and health policy, assist physicians and health care professionals in the treatment of persons with OUD, and to support individuals with OUD in their effort to live a healthy life. Trial registration: ClinicalTrials.gov: NCT04199728. Registered 16 December 2019, https://clinicaltrials.gov/study/NCT04199728?term=NCT04199728.Protocol Version10 May 2023

Determinants of adoption of food safety practices among clam sellers in Kpong and Atimpoku, Ghana

The food safety practices used by clam merchants in Kpong and Atimpoku, Ghana, pose a risk to public health. The study sought to identify factors affecting food safety practices, obstacles to their implementation, and ways of improving them to avoid food-borne infections and promote sustainable practices and development among clam sellers in Kpong and Atimpoku, Ghana. The cross-sectional survey combined purposive and random sampling methods. Sixty-three clam merchants were interviewed face-to-face using a structured questionnaire. Response bias and generalizability to other Ghanaian regions form the study's limitations. Utility maximizing is used to examine how clam vendors adopt food safety procedures. The discrete choice logit model is used to identify food safety decision-making elements. The study examines the extent and significance of relationships between independent factors such as public health officer visits and formal access to credit. The utility maximization paradigm helped to explain clam dealers' food safety measures in Ghana. The study found that age and household size influence worker's decisions to cover clams and wear clean aprons or not. Credit and income-generating activities encourage the wearing of clean aprons. Public health officer visits, clam selling association membership, selling hours per day, availability to finance, and household size on the other hand affect food safety measures when diarrhoea strikes. It is therefore concluded that credit and household size promote better clam seller hygiene. Therefore to promote food safety, policy-makers and stakeholders should offer support, education, and training. This study adds to the literature and emphasizes the significance of food safety standards to safeguard customers and public health.

Digital transformation for safer circular lithium-ion battery supply chains: a blockchain ecosystem-data perspective

Lithium-ion battery (LIB) circular supply chains (CSCs) present unique safety challenges among operation processes. Blockchain technology can be a promising solution for addressing these challenges, by enabling effective tracking and verification of safety-related information throughout the supply chain. However, how blockchain can mitigate safety issues from a supply chain perspective is poorly understood. This study proposes a theory-supported framework through intervention-based research (IBR) to provide guidance for LIB CSC safety management. The conceptual framework and theoretical propositions set the foundation for research on a comprehensive blockchain ecosystem specifically designed for CSC safety management. The framework includes the design of a blockchain architecture with capabilities tailored to address safety concerns, the involvement of multiple stakeholders, and the development of a safety measurement matrix. This study suggests research and practical directions which lay the groundwork for leveraging blockchain technology to improve safety management in LIB CSC. This research contributes to sustainable supply chains by proposing a conceptual framework for mitigating safety concerns in LIB CSC, paving the way for effective blockchain implementation. In addition, this study contributes to advancing the theoretical design understanding and application of blockchain technology in CSC safety management.

Real-time path planning for autonomous vehicle off-road driving

Background Autonomous driving is a growing research area that brings benefits in science, economy, and society. Although there are several studies in this area, currently there is no a fully autonomous vehicle, particularly, for off-road navigation. Autonomous vehicle (AV) navigation is a complex process based on application of multiple technologies and algorithms for data acquisition, management and understanding. Particularly, a self-driving assistance system supports key functionalities such as sensing and terrain perception, real time vehicle mapping and localization, path prediction and actuation, communication and safety measures, among others. Methods In this work, an original approach for vehicle autonomous driving in off-road environments that combines semantic segmentation of video frames and subsequent real-time route planning is proposed. To check the relevance of the proposal, a modular framework for assistive driving in off-road scenarios oriented to resource-constrained devices has been designed. In the scene perception module, a deep neural network is used to segment Red-Green-Blue (RGB) images obtained from camera. The second traversability module fuses Light Detection And Ranging (LiDAR) point clouds with the results of segmentation to create a binary occupancy grid map to provide scene understanding during autonomous navigation. Finally, the last module, based on the Rapidly-exploring Random Tree (RRT) algorithm, predicts a path. The Freiburg Forest Dataset (FFD) and RELLIS-3D dataset were used to assess the performance of the proposed approach. The theoretical contributions of this article consist of the original approach for image semantic segmentation fitted to off-road driving scenarios, as well as adapting the shortest route searching A* and RRT algorithms to AV path planning. Results The reported results are very promising and show several advantages compared to previously reported solutions. The segmentation precision achieves 85.9% for FFD and 79.5% for RELLIS-3D including the most frequent semantic classes. While compared to other approaches, the proposed approach is faster regarding computational time for path planning.

Channel Sinuosity Effects on Inland Transport in the Riverine Region of Ilaje, Nigeria

Transportation is an essential tool for regional social and economic growth, as well as national development. Transport has a vital social and environmental impact that cannot be overlooked. The character of naturally functioning rivers varies greatly and does not remain constant since it is mainly determined by several of physical factors and processes, among which is river sinuosity. Understanding how the inland waterways change with time and the effect or consequences of these changes on the lifestyle and economic activities of the inhabitants becomes very important. This study focused on revealing the changes that had occurred in the planforms of Igbokoda-Idiogba/Ayetoro waterways in Ilaje, Ondo state; its effects on inland transport taking cognisance of sinuosity index. It assessed morphological changes of navigable rivers in the study area from 1972-2022; the effects of river sinuosity on inland transport in the study area were considered. The study deployed geospatial techniques to assess the decadal changes of changing patterns of the channel’s sinuosity taking cognizance of the sinuosity index and formula. However, the study shows the capabilities of geospatial techniques in monitoring river morphology. The study revealed significant changes in the channel’s sinuosity and consequential effects of the changes. Sustainable transport measures for safety and efficiency were recommended.

Near miss road traffic accidents and associated factors among truck drivers in Gamo zone, southern Ethiopia by using a contributory factors interaction model.

Road traffic accidents (RTAs) are among the leading causes of injuries, fatalities, and the resulting increase in financial burdens worldwide. Every year, RTAs cause numerous serious injuries and fatalities in Ethiopia. it is important to understand how prevalent near-miss crash accidents are, and which by definition could have injured the victim but did not result in an actual accident. The determinants of these near-misses are essential in road crash accident reduction strategies. In spite of the fact that near-miss accidents are much more common than actual losses or injuries, very little research has been conducted on them. Thus, this study was intended to assess the near-miss accidents and associated factors among truckers in Gamo zone, southern Ethiopia. The community-based cross-sectional study was employed from May 12 to July 10,2022, using a structured interviewer-administered questionnaire. A simple random sampling technique was used to select participants. The data were analyzed using the statistical package for social sciences. A binary and multivariate logistic regression model was used to identify the determinants of near-miss accidents. A statistical significance level was set at p < 0.05. About 72.5% of truckers had experienced near-miss road traffic accidents. The majority of the near-miss accidents were caused by speeding, followed by driving on the wrong side of the road and skidding, 65 (22.6%), 39 (13.5%), and 38 (13.2%), respectively. Driving frequency per week, location of accidents, condition of the road, sleeping status, and weather conditions were significantly associated with near-miss accidents. The prevalence of near-miss accidents is high in the Gamo zone. Being a younger and less educated driver, high driving frequency per week, driving on major roads and junctions, foggy weather, and inadequate sleep all contribute to the occurrence of accidents. Road safety measures that could address these identified factors are required to mitigate potential RTAs.

ANALYSIS OF UNCERTAINTY IN THE DETERMINATION OF THE CRITICAL YAW RADIUS USING MONTE CARLO SIMULATION

Background: The speed of a vehicle in a curve can be estimated by analysing yaw marks, which indicate its orientation around the vertical axis. When it exceeds the "critical speed," the vehicle slides laterally, evidenced by the oscillation of the rear tires relative to the front ones. Aim: To present a methodology for reconstructing yaw accidents, with an analysis of uncertainties. Methods: This article uses Monte Carlo simulation software to address uncertainties in determining the critical yaw speed of vehicles. The radius of curvature is calculated considering the chord, average arrow, and vehicle gauge, while the road is characterized by negative superelevation and specific friction coefficient. The simulation models input variables with probabilistic distributions, analysing uncertainties related to road characteristics, vehicle properties, environmental conditions, and measurement errors. Results: The simulation results provide a detailed assessment of the uncertainties involved in determining the critical yaw speed, highlighting the importance of a probabilistic approach to ensure a more realistic and reliable assessment of vehicular safety. Discussion: When evaluating measurement uncertainties, it is essential to consider the sensitivity coefficient to ensure a precise and comprehensive analysis of uncertainty sources. Conclusions: This study highlights the importance of analysing and controlling critical variables, such as the radius of curvature and friction coefficient, to accurately determine the critical yaw speed and ensure reliable vehicular safety measures..

Private housing compliance with public seismic safety measures after 2015 Gorkha earthquake in Nepal

After the Gorkha earthquake in 2015, the Nepalese government introduced a series of seismic-resistant building designs to reconstruct and repair residential dwellings. The objective of this research was to explore the extent of compliance with the new prescribed or recommended seismic-resistant features in rebuilt residential structures in two Nepal districts that were severely damaged during the earthquake. The primary source of data was a field survey conducted with a structural questionnaire among 332 affected households during October and November 2022. The survey also utilized informal interviews at three study sites in August 2023, with results showing that 95%–97 % of total respondents reconstructed their houses according to earthquake-resistant standards. The same percentage of respondents withdrew the final payment from the National Reconstruction Authority (NRA). Most reconstructed houses were smaller than before the earthquake; many respondents rebuilt one-room, one-story structures. In addition, housing typologies at the study sites changed from brick/stone and mud-based masonry to cement-based construction. Key Words: Gorkha earthquake, seismic-resistant guidelines, compliance with government safety measures, reconstructed houses, NRA.

A qualitative exploration and a Fuzzy Delphi validation of high-risk scaffolding tasks and fatigue-related safety behavioural deviation among scaffolders

BackgroundMost construction mishaps were caused by scaffolding incidents despite implementing various safety measures, and the association with human factors like fatigue has been widely reported. This study aims to identify all high-risk task sequences involved during the erection of the most commonly used scaffold; the deviation from the standard protocol led to a substandard fatigue state, followed by content validation using the Fuzzy Delphi Method. MethodsQualitative exploration was conducted via focal group discussions (FGDs) involving 30 certified experts. The findings generated from FGDs were further validated by utilising the Fuzzy Delphi Method (FDM) by consulting 19 experts with extensive practical experience and leadership roles in scaffolding safety. ResultsThe FGDs identified a total of 7 constructs and 50 items for task sequences involved in the tubular scaffold erection, namely construct Instruction (3 items), Preparation (3 items), Foundation (10 items), First Lift (8 items), Working Platform (7 items), Guardrails (5 items) and Second Lift (14 items). In the FDM validation process, the experts' consensus for each construct was fulfilled with a threshold value (d) ≤ 0.2; thus, all constructs were accepted. Experts' consensus for all items achieved an expert agreement of 75 % and above. Items ranking was conducted using average fuzzy numbers. The highest average fuzzy number documented was 0.8, while the lowest was 0.588. None of the items with the lowest ranking was discarded as all items perfectly fulfilled the second prerequisite and obtained excellent experts’ agreement. ConclusionsThe tool generated will help guide the development of a protocol for scaffolding safety management.

Hub-and-Spoke Network Design Considering Congestion and Flow-Based Cost Function

This paper presents a model for a “hub-and-spoke network design considering congestion and flow-based cost function”. The number of hubs and spokes is unknown, and the objective is to minimize the cost (including the transportation cost, lost demand, and facility setup cost). In the post-pandemic era, it is expected to have government-imposed restrictions on the congestion of airports, as a measure of health and safety. Unlike the current literature which considers a monetary penalty for congestion, we consider congestion as an externally imposed factor, which should be modeled as a constraint. We take a gravity-based modeling approach to obtain the desirability of a facility and calculate the demand matrix of the network. To solve the model, a Benders decomposition approach is proposed. Without the Benders decomposition approach, only instances with up to ten nodes were solved within a reasonable time, but with the Benders decomposition approach, instances with up to forty nodes were solved. A heuristic algorithm is developed to have a mechanism for dealing with larger instances. A set of experiments are conducted using data from the Turkish Network dataset to study various aspects of the proposed formulation and different parameters’ effects on the performance of the model.

Safe and reconfigurable manufacturing: safety aware multi-agent control for Plug &amp; Produce system

AbstractPlug &amp; Produce aims to revolutionize manufacturing by enabling seamless machine integration into production processes without extensive programming. This concept, leveraging multi-agent systems (MAS), offers increased flexibility and faster production ramp-up times after reconfiguration. As automated manufacturing moves towards greater human integration, this paper addresses safe operation within the Plug &amp; Produce concept. The main safety challenge arises from autonomous decision-making, as agents in the MAS lack awareness of the risk consequences of their behavior. Additionally, the difficulty of perceiving the system’s exact behavior leads to the implementation of overly restrictive safety measures. This limits the system’s flexibility and ability to make decisions for efficient production. This paper proposes a method utilizing multi-agent control to conduct automatic safety analysis and reason task allocations to avoid risks. The method’s benefits are the generation of control actions that comply with safety requirements during operation, eliminating the need for overly restrictive safety measures and allowing more effective equipment utilization. The method’s benefit is illustrated through a manufacturing scenario with two different configurations: one using a hazardous machine and the other using a less hazardous one. Formal verification using the model checker NuSMV demonstrated that safety requirements were satisfied in both configurations, without the need for manual modifications of the safety control system after reconfiguration. The results for this specific manufacturing scenario showed that there are more reachable states (20 states) in the safer second configuration, compared to the first configuration (16 states). This means that the presented control strategy dynamically adjusts the system’s behavior to confirm safety. Hence, this method maintains safety without fixed safety rules that limit the operations.

Comprehensive Study of Load Characteristics of O-type Rotor Car Dumper Based on Measurements

The car dumper, an essential apparatus for unloading bulk materials, is increasingly critical across various sectors such as electricity generation, metallurgy, and operations at port terminals. This significance stems from its continuous operational capacity, which significantly boosts the efficiency of bulk material handling and optimizes the overall processes at industrial sites. This research paper delves into the power quality problems associated with car dumper applications, particularly focusing on the harmonic disturbances caused by inverters used within these systems. Such disturbances can degrade the quality of power within the industrial grid, potentially leading to inefficiencies and safety hazards. To address these issues, the paper proposes the use of parallel active power filters (APF). These filters are renowned for their efficiency in controlling and mitigating harmonic disruptions in electrical systems. The implementation of APFs has shown promising potential to stabilize power quality by filtering unwanted harmonic frequencies and allowing for a smoother power flow. Through detailed measurements conducted on an O-type rotor quad car dumper, the study systematically analyzes the operational characteristics of the dumper, thereby forming a comprehensive database. This database aids in the optimization of electrical control strategies and operational methodologies for car dumpers.The primary objectives of this research are to enhance the operational efficiency of car dumpers, minimize their energy consumption, and improve overall safety measures. By integrating advanced harmonic control technologies such as APF, this study not only addresses the immediate issues of power quality but also contributes to the broader goal of sustainable and efficient industrial practices. The findings are expected to influence future designs and operations of car dumpers, making them more energy-efficient and less prone to electrical disturbances, thereby ensuring a safer working environment in industries dependent on heavy machinery for bulk material handling.

Epidemiological and etiological factors of various fractures and its pharamacological treatment options in a tertiary care teaching hospital - a prospective cohort study

A fracture is a broken bone that can range from a thin crack to a complete break bone. A fracture can occur crosswise, length wise in several parts and in too many pieces. Causes of fracture include physical trauma, accidental fall, sports injuries, stress, and osteoporosis. Fractures can be treated with Medications and lifestyle changes. The objective of the study was to identify common types of fractures mostly affected by people, reduce the incidence rate of fractures and to provide patient counseling regarding precautionary measures to avoid accidents and assaults. In the study period, 120 fracture cases were collected, of this 64 (53.33%) are males and 56 (46.66%) are females. Higher incidence of fractures 27 (22.5%) occurred in 50-60 years of age group. Major fractures 48 (47.5%) were occurred due to trauma. 21 (17.5%) were diagnosed by X-rays, 15 (14.5%) patients are diagnosed by CT scan. 22 (18.33%) patients are categorized under femur bone fractures. 52(43.3%) patients were treated with NSAIDS, 33 (27.5%) patients were treated with antibiotics. 29.33% were treated with vitamins and mineral supplements. The study concludes that out of 120 study subjects, major fractures were occurred due to trauma. Clinical pharmacists and other health care professionals intervention to create awareness regarding fractures, medications, lifestyle modifications and other safety measures helps them to recover faster from fractures.