Forestry 5.0 and the human factor: a critical review of digital technologies in occupational safety and health management

Abstract

Introduction:

Despite widespread mechanization, safety improvements in forestry have stagnated. The emerging “Forestry 5.0” paradigm offers a human-centric approach to digital transformation, yet its application in occupational safety and health remains limited. This study critically reviews recent digital advancements to evaluate their potential in shifting safety management from reactive compliance to proactive resilience.

Methodology:

A systematic review was conducted following PRISMA guidelines. Literature published between 2021 and 2025 was retrieved. From an initial screening of 3,328 records, 19 key studies were selected to analyze specific technological interventions and risk dynamics.

Results:

The analysis classifies risks into six dimensions and identifies three core technological clusters: intelligent detection, predictive analytics, and smart protective systems. While these innovations effectively mitigate physical hazards, results indicate the emergence of “insidious risks,” including cognitive overload and reduced situational awareness. Consequently, digitalization may unintentionally displace dangers from the physical to the psychological domain.

Discussion:

Technological advancement alone is insufficient for safety assurance. A “Human-in-the-Loop” framework is proposed, concluding that sustainable occupational safety and health requires integrating digital tools with a robust safety culture. Future implementation must prioritize intuitive human-machine interfaces and integrate digital tools with worker-centered strategies, ensuring technology augments rather than overrides human judgment.

1 Introduction

The forestry sector faces a critical challenge: balancing the demand for sustainable bioeconomy outputs with its persistent status as one of the world’s most dangerous industries. Although mechanized harvesting is now widespread, the unstructured and dynamic nature of forest environments continues to pose severe physical risks to workers from unstable terrain to climate change-induced extreme weather (Garland et al., 2020; El Khayat et al., 2022). While mechanization has reduced injuries from manual labor, it has not significantly lowered high fatality rates in these complex settings, indicating that conventional safety measures have yielded most of their potential benefits (Albizu-Urionabarrenetxea et al., 2013; Di Stefano et al., 2025; Moos et al., 2023). This stalled progress in safety outcomes highlights a systemic failure to address evolving risks, calling for a fundamental shift from reactive mitigation to proactive, data-driven safety management.

Alongside these challenges, the rise of digital technologies—often termed Forestry 4.0—is transforming forestry’s information landscape. The integration of the Internet of Things, blockchain, and remote sensing has been primarily focused on boosting supply chain efficiency and monitoring resources (Damaševičius et al., 2024). Yet, their application as proactive safety tools remains underdeveloped. For instance, while real-time data is increasingly used to track forest health and carbon stocks (Zweifel et al., 2023), its use in monitoring the well-being of the workers within that ecosystem has not kept pace. This gap between technological potential and practical safety use is critical; digital transformation must expand beyond resource management to protect workers’ health and safety.

In 2021, the emerging Industry 5.0 paradigm offers a framework to bridge this divide by placing human well-being at the core of technological progress. In contrast to the automation-centric Industry 4.0, Industry 5.0 emphasizes human-centricity, resilience, and sustainability, promoting technologies that collaborate with people rather than replace them (Breque et al., 2021; Nasir et al., 2025). Similar to the field of forestry, the relationship between the two is evolutionary rather than competitive: while Forestry 4.0 focuses on building the digital infrastructure for operational efficiency and yield maximization, Forestry 5.0 leverages this connectivity to prioritize the human operator, shifting the focus from system optimization to worker preservation (Xu et al., 2021; Leng et al., 2022). Applied to “Forestry 5.0,” this means deploying smart personal protective equipment, wearable sensors, and exoskeletons that augment workers’ physical abilities and provide real-time physiological monitoring (Holzinger et al., 2024; Okpala and Nnaji, 2024). The significance of this approach is its potential to turn occupational health and safety management into a dynamic, adaptive process that responds to worker fatigue and environmental threats as they occur.

Unlike controlled factory settings, there is still a lack of robust empirical evidence to confirm digital technologies’ effectiveness in real-world harvesting operations. Moreover, adopting these digital solutions without critical oversight introduces new, subtle risks. In the rugged, unpredictable context of forestry, complex human-machine interfaces may impose significant mental demands on workers. While specific empirical evidence in forestry is still emerging, studies from the construction industry—which share similar dynamic and unstructured characteristics—indicate that managing mental workload is critical for preventing safety incidents (Chen et al., 2017). Drawing on these parallels, the potential for digital notifications to compete for workers’ attention suggests that cognitive overload and reduced situational awareness represent critical emerging risks that must be proactively managed to prevent replacing physical dangers with psychological and cognitive ones (Okpala and Nnaji, 2024). In other words, rather than having inevitable consequences, these issues represent critical emerging risks that must be actively addressed.

This study examines the critical intersection of digital transformation and occupational safety through a systematic review of emerging “Forestry 5.0” technologies. We assess how human-centric innovations, particularly intelligent detection, predictive analytics, and smart protective systems, can address the sector’s persistent physical and psychosocial risks while promoting a resilient safety culture. The study is structured as follows: Section 2 outlines the systematic review methodology; Section 3 categorizes key occupational risks and examines the current landscape of safety technologies and culture; Section 4 analyzes the gap between technological potential and practical implementation; and Section 5 concludes with strategic recommendations for integrating human factors into the digital forestry ecosystem.

2 Methodology

The process of research methodology is carried out as shown on Figure 1. At first, we performed data searching based on words and operators, and then completed the data cleaning through the outlier and duplication check. After the above processes, we obtained the initial records and identified the selected records according to exclusion and inclusion criteria. Afterwards, we obtained the targeted studies for further analysis.

Figure 1

Studies on the fields of digital technology and occupational health and safety in forestry workers were searched and identified in the Web of Science (WOS) Core Collection and China National Knowledge Infrastructure (CNKI). Specifically, WOS Core Collection is one of the most authoritative citation information sources worldwide, and contains over 10,000 multi-disciplinary, high-quality, wide-impact international comprehensive academic journals (Zhao et al., 2017; Zhang et al., 2021). It is representative of high-impact, internationally circulated scholarly literature, primarily in English. Its core collection (SCI, SSCI, AHCI) is highly selective. CNKI is licensed by the National Press and Publication Administration (NPPA) and is deeply integrated into China’s state-supported knowledge infrastructure. It is highly representative of the comprehensive output of Chinese scholarly and intellectual activity, as well as operates 10 global service centers and serves users across universities, research institutions, government think tanks, and industries worldwide; its daily download volume exceeds 5.7 million, and it consistently ranks among the top 3 global academic websites in terms of visit volume (Liu, 2024). In this study, WOS Core Collection and CNKI were chosen together: based on WOS Core Collection database, we can grasp the global research frontiers, highly cited works, and international academic discourse; while for CNKI database, we can gain a comprehensive understanding of the research panorama of Chinese scholars in related fields, as well as the policy background and local considerations. The two are complementary rather than substitutive, jointly forming the complete information map of academic research. The peer-reviewed articles in these two databases may have overlapping or complementary contents. Conducting cross-validation can make the systematic review more comprehensive and reliable (Qazi and Appolloni, 2022).

The search codes were used as follows (Figure 2): TS (Topic Search) = (Forest* OR Logging), TS = (Safety OR Risk), TS = (Technolog* OR UAV OR AI OR Computer Vision OR Digital Twin). The above four sets of search results were combined with “AND” to select articles that meet both criteria. The asterisk (*) serves as a wildcard or truncator, enabling automatic matching of keywords that commence with the preceding word before the (*) operator. The same search was also conducted using Chinese synonyms, in the CNKI database. After searching, 3,328 studies were identified.

Figure 2

Figure 3

3 Results

A total of 3,328 records were retrieved during the initial search. After the selection process, 19 of these studies aim to assess the digital advances in occupational health and safety technology in tree and forest work. In this section, we elaborate in the following aspects in detail: Multidimensional category risks, advances in safety technologies, and safety culture.

3.1 Multidimensional category risks

Based on the analysis of selected articles, the occupational and safety risks in forestry work can be classified into six major categories: Physical risk, technical risk, biological risk, chemical risk, psychological risk, and organizational risk. Table 1 provides the characteristics and findings of multidimensional occupational and safety risks in tree and forest work, especially in the process of digitization.

Physical risk is a relatively traditional type of risk faced by forestry workers, due to the particularity of the working environment: for instance, the complex terrain increases the likelihood of personnel falling accidents (Unver and Ergenc, 2021; Zhao et al., 2025). Several studies proposed that vibration and noise in the forestry work environment causes sensory deterioration, such as, high frequency hearing loss (Scott et al., 2022). For example, the study of Knecht et al. (2024) indicated that the prevalence of hearing loss in forestry workers was about 21, and 33% of mechanized loggers were exposed to excessive noise during a 12-h shift. For the risk of high temperature, Lima et al. (2023) demonstrated during the high temperature period, the frequency of unsafe behaviors was the highest, especially in logging and pre-skidding. Moreover, heat stress caused by high temperature and humidity leads to the removal of personal protective equipment (e.g., earmuffs and protective clothing), making it more likely that protection fails (Lima et al., 2023).

For forestry workers, the most common technical injuries were hand saw cuts, followed by electric saw burns and eye injuries; while receiving training in occupational safety and first aid courses is regarded as an important solution to avoid technical risks (Staněk et al., 2022). In the tree and forest work environment, incorrect logging theories often result in fallen branches or logs during the work process, causing casualties (Unver and Ergenc, 2021). Besides, frequent mechanical failures lead to work interruptions and safety risks (Lima et al., 2023); differences in work equipment also have a differential effect on the load of different types of operators (Mapatunage et al., 2024). Additionally, the effectiveness and improper use of safety protection facilities caused by various human factors also prove that risk management should start from the organization and carry out safety management from the perspective of human beings.

As far as biological risk is concerned, insect and spiders’ bites, as well as tick- and mosquito-borne diseases are the most common work-related injuries, exposing workers to risks of respiratory infections, allergies, and even Lyme disease, encephalitis, etc. Study of Knecht et al. (2024) pointed that over 90% of forestry workers reported being bitten by hymenopteran insects; while treated clothing with permethrin provided 82% protection against ticks. Additionally, although much of studies have focused on the health risks during the storage and consumption stages of biomass in the tree and forest work environment, there has been insufficient attention paid to the large number of harmful microorganisms that grow in wood piles during storage: their spores can spread up to 300 meters away, posing a great health threat to workers and even nearby residents (Gejdoš and Lieskovský, 2024).

Chemical risks may be one of the relatively less encountered occupational health and safety risks for forestry workers; since studies have shown that health risks related to the chemical environment in forestry work in Southeast Asia account for only 1% (Kaakkurivaara et al., 2022). Nevertheless, chemical risks still pose a threat. For example, pesticide exposure during the planting stage (such as glyphosate) is proven associated with cancer and respiratory diseases (Gejdoš and Lieskovský, 2024). Besides, fuel and asbestos are both major sources of chemical exposure, causing respiratory diseases among forestry workers: studies have shown that many of logging workers reported symptoms and allergy related to diesel exhaust and chain saw smoke exposure (Unver and Ergenc, 2021; Gejdoš and Lieskovský, 2024).

The psychological risks about occupational health and safety resulting from job burnout, such as sluggish reactions and deteriorating mental health, are usually not given sufficient attention due to their potential and long-term features (Bielinis et al., 2025). According to Korneeva et al. (2022), psychosocial risks include monotonous work content, high attention requirements, leadership deficiency, rigid organizational culture, bullying and harassment, etc.; in extreme circumstances, psychosocial risk management serves as an important supplement to traditional physical risk prevention and control. Besides, studies of Mapatunage et al. (2024) and Scott et al. (2022) demonstrated that the potential causes of the chronic health problems of workers might be the physiological burden resulting from long-term moderate-to-high-intensity psychological stress. Furthermore, once a work-related injury occurs, 71% of Latino forestry workers choose not to report it due to excessive psychological stress (such as fear of retaliation), which further increases the likelihood of health hazards occurring in the workplace environment (Knecht et al., 2024).

In the context of working in a forest environment, organizational risks are the primary cause of occupational injury accidents; that is, organizational management failure is the core of the safety issue (Yovi and Yamada, 2019; Kaakkurivaara et al., 2022). It has been proven that the most significant occupational health and safety risks do not always come from tools and technologies; rather, it is the lack of management and human factors that play a dominant role (Unver and Ergenc, 2021). At present, numerous studies have shown that technological advancements have significantly enhanced the safety of work. However, further research indicates that even with advanced technologies, the absence of basic safety management and individual safety awareness still poses extremely high risks (Staněk et al., 2022). Additionally, studies that claim “a certain technology reduces risks through universality” may, due to their “adjustment” or “averaging” analytical methods, mask the differentiated impacts of this technology on specific subgroups (Knecht et al., 2024). These studies collectively suggest that technological development must be combined with management and organizational culture, for the effectiveness and sustainability of occupational health and safety management in tree and forest work.

More importantly, occupational health and safety risks in forestry work environment do not exist independently but are intertwined and mutually influential, forming a complex risk network. With the improvement of forestry mechanization and intelligence levels, the traditional acute trauma risks have decreased, but chronic health risks (like musculoskeletal disorders, hearing loss) and psychological-social risks are increasingly prominent (Scott et al., 2022; Mapatunage et al., 2024). In addition, under the backdrop of globalization and climate change, forestry risks present characteristics of cross-regional, cross-seasonal, and increased uncertainty. However, traditional risk management mostly adopts a reactive approach and a single risk control model, lacking systematicity and foresight (Kaakkurivaara et al., 2022; Scott et al., 2022; Gejdoš and Lieskovský, 2024). Also, insufficient attention is paid to psychological and social factors as well as organizational culture, and the social construction attribute of risks is overlooked (Korneeva et al., 2022; Staněk et al., 2022). Thus, there is a disconnection between technological application and management measures, and no synergy effect has been achieved.

3.2 Advances in safety technologies

According to the analysis of selected articles, the advanced technologies applied in forestry work to enhance occupational health and safety are classified into the following three categories: Intelligent detection and perception, risk assessment and prediction, safety protection and intervention. Figure 4 illustrates the logical connections and specific connotations of these categories of technologies.

Figure 4

3.2.1 Intelligent detection and perception

Drone, computer vision, and physiological and environmental monitoring technology are regarded as the three markedly promising intelligent monitoring and sensing technologies in this field of tree and forest work. Specifically, in terms of forest fire monitoring, the combination of drones and AI enables near-real-time monitoring, thus significantly improving the accuracy of early detection as well as workers’ safety (Buchelt et al., 2024). Besides, due to the particularity and complexity of the forestry work environment, the complex environment navigation technology is applicable to the fully autonomous navigation system for environments without GNSS signals and with drastic changes in lighting conditions under the forest canopy (Zhao et al., 2025). In addition, drones can also be used for search and rescue and wildlife monitoring, enhancing emergency response efficiency and reducing personnel exposure risks (Buchelt et al., 2024).

As one of the computer vision technology, posture monitoring technology can achieve real-time identify high-risk musculoskeletal postures, such as the application of the Media Pipe framework in the posture assessment of mobile manual skinning workers, which enables real-time intervention of improper postures, thereby reducing the risk of chronic diseases (Gülci et al., 2025). Likewise, risk scenario identification automatically identifies potential risk factors in the working environment through image analysis (Zheng et al., 2022); equipment status monitoring judges the operating status of equipment based on visual features and predicts fault risks (Zhao et al., 2025).

Physiological and environmental monitoring technology have demonstrated significant advantages in monitoring the health status of people and environmental risks in forestry work environments. For example, workload assessment, combined with the NASA TLX subjective load scale and heart rate monitoring, can effectively quantify the psychological and physiological load of workers, helping enterprise managers promptly understand the health status of the workers (Mapatunage et al., 2024). Also, health status monitoring tracks long-term health indicators of workers, which contributes to detect occupational disease risks at an early stage (Scott et al., 2022). Moreover, environmental parameter monitoring continuously records environmental parameters such as temperature, humidity, noise, and vibration, warning of risks such as heat stress and noise exceedances (Lima et al., 2023).

3.2.2 Risk assessment and prediction

For a long time, the traditional quantitative assessment method has been the most widely used and recognized approach for researchers to quantify the occupational health and safety of workers in the forestry environment. For instance, the Analytic Hierarchy Process (AHP) model is used for prioritizing risks and providing scientific basis for resource allocation (Unver and Ergenc, 2021). Risk aversion importance sampling method reduces personnel exposure in high-risk areas while maintaining statistical accuracy (Roesch et al., 2023). Multi-criteria decision analysis comprehensively considers multiple dimensions such as technology, economy, and society to assess occupational health and safety risks (Lederer et al., 2022).

With the development of digital technology and the optimization of artificial intelligence models, machine learning algorithms are increasingly being applied in occupational health and safety risk assessment and control in tree and forest work environments. For example, by using algorithms such as backpropagation (BP) neural network and support vector machines, it is possible to predict the probability of occurrence of work-related accident risks, enabling the pre-processing of high-risk accidents and thus improving the efficiency of risk management (Zheng et al., 2022). Likewise, the hybrid model, which combines physical models with data-driven models, can significantly improve the prediction accuracy (Lederer et al., 2022). Furthermore, deep learning model, based on neural networks, is capable of handling complex nonlinear relationships; compared with the traditional ensemble Kalman filtering method that severely underestimates the probability of extreme events, its assimilation accuracy can be greatly improved (Xuan et al., 2024; Zhao et al., 2025).

3.2.3 Safety protection and intervention

The innovations in safety protection and intervention technologies mainly fall into two categories: the innovation of personal protective equipment and of safety technologies for work equipment in operations. For the one side, the intelligent personal protective equipment is equipped with sensors that can monitor the workers’ status and environmental parameters in real time, which helps detect individuals who may be in the risky area in a forest hazardous environment (Lima et al., 2023; Hönigsberger et al., 2025). The ergonomic design reduces the restrictions on the workers’ movements caused by personal protective equipment, thereby enhancing the usage compliance (Bacic et al., 2024; Çakit and Karwowski, 2025; Gülci et al., 2025). The integrated functions enable multi-functional protection and address various risks simultaneously (Pavlíková et al., 2024).

For the other side, studies have pointed out that the probability of MSDs (musculoskeletal disorders) among logging workers is extremely high, and lower back pain is the most frequently reported symptom (Kim et al., 2017; Rodriguez et al., 2019); while the use of appropriate mechanized equipment can significantly reduce the risk of MSDs (Knecht et al., 2024). Specifically, automation and intelligence reduce manual intervention and lower the risk of operational errors (Hoenigsberger et al., 2024). The optimization of human-machine interaction adopts ergonomic equipment design to reduce musculoskeletal injuries (Bacic et al., 2024; Gülci et al., 2025). Moreover, the fault self-diagnosis and warning technology enables the equipment to automatically detect faults and issue warnings, thereby preventing accidents from occurring (Zhao et al., 2025).

Nevertheless, the impact of innovations in safety protection and intervention technologies on forestry occupational and safety risk management is two-sided. On one hand, the advanced protective measures and techniques have indeed significantly improved the working environment and enhanced the health of the workers (Buchelt et al., 2024; Gülci et al., 2025). On the other hand, it is proven that even with advanced technology, the absence of basic safety management and personal safety awareness still results in extremely high occupational health and safety risks (Staněk et al., 2022). Also, the mechanization and digitization of forestry do reduce acute injuries, but might give rise to new chronic health problems, such as hypertension and obesity (Scott et al., 2022; Mapatunage et al., 2024).

3.3 Safety culture

Many scholars believe that psychological and organizational factors in forestry work have a highlighted impact on the effectiveness of occupational health and safety management. Herein, safety culture has become one of the key terms discussed in this field; while the core elements of safety culture can be classified into: leadership and organizational support, communication and participation, training and capacity building, and collaboration between technology and management.

First, top-down occupational health and safety management and culture building are regarded as authoritative measures (Flores and Haire, 2021); yet workers and leaders in forestry industry have different views on occupational hazards and safety management (De Castro et al., 2023). Anyway, in terms of leadership behavior, the support and participation in decision-making by immediate supervisors can significantly enhance work performance and reduce stress, and the high attention and adequate resource investment from leadership in occupational health and safety are the firm foundation of safety culture construction (Korneeva et al., 2022). Besides, institutional guarantees require well-developed safety management systems and procedures, being conductive to improve the safety and health of workers, thereby reducing the corresponding rates of occupational accidents and occupational diseases (Lima et al., 2020).

Second, the construction of safety culture requires communication and participation from all members of the team. As a foundation, two-way communication requires the establishment of a smooth channel for secure information exchange; while new information and communication technologies, such as Forestry 4.0, have made it more convenient and easier (Laroche et al., 2020; Erber et al., 2025). Additionally, the low level of employee participation in safety decisions and the lack of feedback have led to in-negligible issue on psychological and social risks, thereby affecting the effectiveness of safety management (Korneeva et al., 2022).

Third, forest workers received safety training demonstrate significantly higher emergency response capabilities compared to others, that is, targeted work training, provided based on the risk characteristics of different positions, has a particularly positive effect on enhancing occupational health and safety (Staněk et al., 2022). Moreover, the enhancement of safety capabilities requires continuous learning, thus the continuous occupational health and safety learning mechanism needs to be established (Cha et al., 2025). Meanwhile, conducting emergency drills regularly could not only test the learning outcomes of workers’ occupational health and safety knowledge, but also significantly enhance their emergency response capabilities.

Fourth, the construction of safety culture in the forestry sector requires the synergy and integration of technology and management. Specifically, advanced digital technology provides data support for safety management: by using intelligent monitoring technology to obtain real-time data, management decisions can be supported (Roesch et al., 2023; Buchelt et al., 2024). In return, safety management provides application scenarios for digital technologies: clear management requirements guide the direction of technological research and application (Gejdoš and Lieskovský, 2024; Mapatunage et al., 2024). By integrating technology with management, the maximum effectiveness of safety culture can be achieved, and sustainable development of occupational health and safety management can be realized (Staněk et al., 2022).

4 Discussion

The main objective of this systematic review is to understand the current development status of occupational health and safety in tree and forest environment, especially in the context of the rapid development of digital technology, for promoting efficient and sustainable safety management as well as proposing the promising research trends. An analysis of the current data reveals four main findings.

First at all, several studies have reported the difficulties in obtaining data for research on occupational health and safety in forestry environment, but there are few advanced methods to address this issue. Given this scarcity of forestry-specific empirical data, insights must be extrapolated from adjacent sectors with similar high-risk profiles. In some other working environments like manufacturing (Tang et al., 2023), construction (Abanda et al., 2025), and power (Jia et al., 2025), enterprises can collect health and safety data related to employees’ status through the methods of digital twins (Abanda et al., 2025), digital phenotyping (Alam et al., 2025) and industrial Internet of Things (IoT; Sharma and Villányi, 2024); while based on these data, carrying out efficient safety management and risk control. However, due to the particularity of the forestry work and various difficulties such as complex terrain, time sensitivity, and response latency, these technologies may be temporarily difficult to be widely adopted (Buchelt et al., 2024). Besides, by referring to the research and practices of the agriculture and fisheries industries, applied the detailed AI algorithm toolbox (such as Random Forest for risk prediction, Convolutional Neural Network for image recognition) and technology integration paradigm (Computer Vision collaborates with the IoT for real-time monitoring) in tree and forest environment are possible to be the promising directions for safety data collection (Buchelt et al., 2024; Kilinc et al., 2025). For example, applying computer vision to analyze the postures of logging machine operators (in line with Gülci et al. (2025)), or using AI to predict the organizational risk factors in forestry work; thereby promoting the digitalization and sustainability of occupational health and safety management. Nevertheless, the most important thing is that more attention should be focused on the application and popularization of special and targeted digital technologies in the forestry environment; otherwise, the limitations of methods would make it difficult for occupational health and safety management to proceed in an orderly manner.

In addition, the improvement of workers’ safety awareness has not kept pace with the rapid development of technology. Previous studies have demonstrated that in the forestry environment, if there is a lack of basic safety management and personal safety awareness, even with advanced technologies, the health risks of injury for workers remains extremely high (Scott et al., 2022; Staněk et al., 2022). Similarly, research on other industries has further demonstrated that the impact of advanced digital technology on the health and safety of the professional environment is not entirely positive, while the human factor is the primary source of safety risk (Ranasinghe et al., 2023; Jiang et al., 2024). Crucially, the introduction of complex digital interfaces may introduce new, subtle hazards. Drawing on evidence from the construction sector, studies indicate that the continuous influx of data from wearable sensors can inadvertently increase workers’ mental workload, potentially leading to cognitive overload and reduced situational awareness (Chen et al., 2017). Therefore, rather than assuming digitization automatically equates to safety, these issues should be treated as critical emerging risks in forestry that require proactive management. That is, digital technology has significantly enhanced safety in production by replacing dangerous tasks with advanced tools (Liao and Cai, 2024); however, the lack of safety awareness may lead to people’s resistance toward technology (due to insufficient understanding of technology and concerns about the privacy issues), thus resulting the effectiveness of digital health risk tools has been greatly reduced (Grosman-Rimon and Wegier, 2024). In that case, strengthening the safety training for enhancing workers safety awareness, rather than blindly introducing advanced digital technologies for risk monitor and control, has become the most crucial part in forestry occupational health and safety management. Existing studies have pointed out, digital technologies take advantages on safety training by applying Augmented Reality (AR) and Virtual Reality (VR) for offering an active, immersive, and interactive learning environment (Gong et al., 2024; Yang and Fan, 2025), which not only provides effective safety training for workers, but also reduced their resistance to digital tools by increasing the frequency of interaction between workers and digital technology. The integration of digital technology and education for safety awareness is the key to achieving a win-win situation for sustainable occupational health and safety management.

What’s more, psychological risk at work is one of the crucial causes of occupational accidents, while organizational factors are believed to either intensify or alleviate the psychological risks faced by workers; that is in line with the viewpoints of studies by Vveinhardt and Sroka (2017), Anders et al. (2024) and Dardzińska-Głębocka et al. (2025). It is said that an organization with outstanding commitment is probable to have a direct positive impact on job satisfaction and psychological safety for employees (Fraboni et al., 2023; Yang et al., 2024); in reverse, one with disorganized organization and unfairness is more likely to cause depression, anxiety, job burnout, and finally chronic occupational diseases among employees (Sherwood et al., 2019; Catapano et al., 2023). For instance, study of Magnavita et al. (2022) demonstrated, the quality of work organization not only leads to a decline in productivity, but also increases the risk of mental and physical disorders; thus, the continuous improvement of work organization must take the well-being of workers into account. Furthermore, the insufficient attention given to workers’ mental health within the organization has proven a reason for the low efficiency of safety management, as previous studies have shown that organizational fairness is one of the potential health risks that can lead to poor mental health states and even physical illness among workers (Kobayashi and Kondo, 2019; Sarfraz et al., 2023). Additionally, Xie and Takahashi (2022) proposed that, work pressure is a psychological factor contributing to early resignation. At present, the rapid loss of labor force is the main challenge that cannot be ignored in the forestry industry (Ayompe et al., 2025; Šporčić et al., 2025); therefore, it is of great significance to enhance the psychological safety of employees at work for the retention of workers.

Last but not least, concerns about data privacy and worker surveillance may pose significant obstacles to the application of digital technologies in forestry health and safety management. The pervasive collection of biometric, positional, and behavioral data through wearables, drones, and IoT sensors raises critical questions about ownership, consent, and ethical use (El Bouchikhi et al., 2024). In many jurisdictions, forestry operations occur in remote or indigenous lands where data sovereignty becomes a pressing issue—unregulated data flows may exploit local communities or violate traditional rights (Adams, 2024). Moreover, continuous monitoring risks fostering a culture of mistrust, where surveillance is perceived as a tool for productivity enforcement rather than a genuine protective measure, which leads to employee resistance, reduced morale, or even intentional circumvention of safety devices, undermining the very purpose of technological intervention (Mettler, 2024). Therefore, establishing transparent data governance protocols, anonymizing data where possible, and involving workers in the co-design of monitoring systems are essential steps to balance safety gains with privacy preservation and ethical responsibility.

Given all these findings, the purpose of this review is not to provide definitive results, but to systematically summarize the early explorations, identify knowledge gaps, and inspire future research agendas. The discussion regarding the technical integration and the necessity of technology collaboration could be regarded as a forward-looking framework and testable proposition based on limited evidence. To advance this field from concepts to robust science and practice, priority should be given to conducting long-term empirical research that is interdisciplinary, well-designed and diverse in background, and unified assessment standards should be established. Only in this way can the potential of Forestry 5.0 be objectively evaluated and effectively realized on a solid and comprehensive evidence basis.

5 Conclusion

The shift to Forestry 5.0 presents a pivotal opportunity to redefine occupational health and safety by integrating digital intelligence with human-centered design. Our review finds that technologies such as computer vision, wearable sensors, and predictive AI show significant potential in reducing physical hazards and improving situational awareness. However, their effectiveness depends fundamentally on the strength of the underlying safety culture and organizational commitment. While these tools enable a shift from reactive compliance to proactive resilience, this transformation can only be sustained through parallel changes in organizational management, ones that treat the “human factor” as the core asset of the forestry value chain.

Yet the digitalization of forestry work also imports a range of subtle but serious risks that challenge conventional safety frameworks. The uncritical adoption of complex monitoring systems could cause cognitive overload, raise data privacy concerns, and further foster an over-reliance on automated alerts, merely substituting physical for psychological risks. Compounding this, the rapid advance of Forestry 4.0 technologies has outpaced the development of worker-centered safety strategies. This growing disconnect threatens to widen the gap between technological potential and real-world applicability, particularly in resource-limited settings.

Achieving a sustainable and safe bioeconomy requires a fundamental shift to a “Human-in-the-Loop” approach in both research and policy. Industry leaders must prioritize interoperable, intuitive interfaces that augment—not override—workers’ judgment, alongside sustained investment in immersive tools to foster digital fluency. Ultimately, the success of Forestry 5.0 will be measured not by its technical sophistication, but by its ability to create resilient and inclusive workplaces where technology steadfastly safeguards human well-being.

Overall, this study represents one of the first systematic attempts to bridge the conceptual gap between “Forestry 5.0” digital transformation and the practical realities of occupational health and safety management. Unlike previous reviews that isolate technological performance from human factors, our work innovatively synthesizes technical advancements with socio-organizational dynamics to reveal the “insidious risks” of digitalization. By classifying multidimensional risks through a dual lens of technological capability and organizational culture, this study proposes a novel “Human-in-the-Loop” framework that redefines digital tools not merely as efficiency drivers, but as active guardians of worker well-being. This point challenges the prevailing techno-centric narrative, offering a new theoretical basis for designing resilient, human-centric safety systems in the bioeconomy era.

Notwithstanding above value-add findings, there are several limitations in this study. First, this review was limited to published peer-reviewed journal articles; this was a deliberate decision to ensure scientific rigour and the reliability of findings. Second, due to the limited research in this field, there are not many studies available for reference. The above two factors together caused that, in this study, the number of samples that met the inclusion criteria was relatively small, leading to incomprehensiveness and generalizability of results: For the one side, the current research evidence is deficient in both breadth (geographical coverage, as the studies dominated by Europe, North America, and China, and diversity of technological applications) and depth (rigor of research design, long-term data). For the other side, the key influencing factors and potential benefits identified currently may be applicable to high-tech and high-investment scenarios similar to those included in these studies, but their applicability in various forest governance systems or resource-limited regions needs to be further tested.

To the best of our knowledge, this study may be one of the first systematic reviews that attempts to elaborate the current research status and promising trends for occupational health and safety risks management in tree and forest work environment within the context of industrial digitalization. This study not only provides the basic theoretical foundation for further research in this field, but also offers the practical guidance for related government and manager to improve the efficiency of occupational health and safety management as well as workers’ well-beings.

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