Improve Delivery Efficiency Research Articles

Design and Implementation of a Community Waimai Delivery Assistant System Based on Path Optimization Algorithm

With the rapid development of the food delivery industry, how to efficiently complete delivery tasks in complex community environments has become an important challenge for food delivery platforms and delivery personnel. This project focuses on the problem of planning delivery routes for b0oth inside and outside residential areas, and designs and implements a delivery assistant system based on the Internet of Things and path optimization algorithms. The system utilizes the DFRobot IoT platform to achieve real-time communication between Python programs and mobile apps. Through various path optimization algorithms such as genetic algorithm and simulated annealing algorithm, the system automatically generates the optimal delivery path, significantly improving delivery efficiency and reducing delivery costs. The experimental results show that the system has good operability and reliability in practical applications, providing an effective solution for improving the intelligence level of food delivery

Proton ARC based LATTICE radiation therapy: feasibility study, energy layer optimization and LET optimization

Objective.LATTICE, a spatially fractionated radiation therapy (SFRT) modality, is a 3D generalization of GRID and delivers highly modulated peak-valley spatial dose distribution to tumor targets, characterized by peak-to-valley dose ratio (PVDR). Proton LATTICE is highly desirable, because of the potential synergy of the benefit from protons compared to photons, and the benefit from LATTICE compared to GRID. Proton LATTICE using standard proton RT via intensity modulated proton therapy (IMPT) (with a few beam angles) can be problematic with poor target dose coverage and high dose spill to organs-at-risk (OAR). This work will develop novel proton LATTICE method via proton ARC (with many beam angles) to overcome these challenges in target coverage and OAR sparing, with optimized delivery efficiency via energy layer optimization and optimized biological dose distribution via linear energy transfer (LET) optimization, to enable the clinical use of proton LATTICE.Approach.ARC based proton LATTICE is formulated and solved with energy layer optimization, during which plan quality and delivery efficiency are jointly optimized. In particular, the number of energy jumps (NEJ) is explicitly modelled and minimized during plan optimization for improving delivery efficiency, while target dose conformality and OAR dose objectives are optimized. The plan deliverability is ensured by considering the minimum-monitor-unit (MMU) constraint, and the plan robustness is accounted for using robust optimization. The biological dose is optimized via LET optimization. The optimization solution algorithm utilizes iterative convex relaxation method to handle the dose-volume constraint and the MMU constraint, with spot-weight optimization subproblems solved by proximal descent method.Main results.ARC based proton LATTCE substantially improved plan quality from IMPT based proton LATTICE, such as (1) improved conformity index (CI) from 0.47 to 0.81 for the valley target dose and from 0.62 to 0.97 for the peak target dose, (2) reduced esophagus dose from 0.68 Gy to 0.44 Gy (a 12% reduction with respect to 2 Gy valley prescription dose) and (3) improved PVDR from 4.15 to 4.28 in the lung case. Moreover, energy layer optimization improved plan delivery efficiency for ARC based proton LATTICE, such as (1) reduced NEJ from 71 to 56 and (2) reduction of energy layer switching time by 65% and plan delivery time by 52% in the lung case. The biological target and OAR dose distributions were further enhanced via LET optimization. On the other hand, proton ARC LATTCE also substantially improved plan quality from VMAT LATTICE, such as (1) improved CI from 0.45 to 0.81 for the valley target dose and from 0.63 to 0.97 for the peak target dose, (2) reduced esophagus dose from 0.59 Gy to 0.38 Gy (a 10.5% reduction with respect to 2 Gy valley prescription dose) and (3) improved PVDR from 3.88 to 4.28 in the lung case.Significance.The feasibility of high-plan-quality proton LATTICE is demonstrated via proton ARC with substantially improved target dose coverage and OAR sparing compared to IMPT, while the plan delivery efficiency for ARC based proton LATTICE can be optimized using energy layer optimization.

Direct delivery of Cas9 or base editor protein and guide RNA complex enables genome editing in the retina

Genome editing by CRISPR-Cas holds promise for the treatment of retinal dystrophies. For therapeutic gene editing, transient delivery of CRISPR-Cas9 is preferable to viral delivery which leads to long-term expression with potential adverse consequences. Cas9 protein and its guide RNA, delivered as ribonucleoprotein (RNP) complexes, have been successfully delivered into the retinal pigment epithelium in vivo. However, the delivery into photoreceptors, the primary focus in retinal dystrophies, has not been achieved. Here, we investigate the feasibility of direct RNP delivery into photoreceptors and RPE cells. We demonstrate that Cas9 or adenine-base editors complexed with guide RNA, can enter retinal cells without the addition of any carrier compounds. Once in the retinal cells, editing rates vary based on the efficacy of the guide RNA and the specific location edited within the genes. Cas9 RNP delivery at high concentrations, however, leads to outer retinal toxicity. This underscores the importance of improving delivery efficiency for potential therapeutic applications in the future.

Polymers as Efficient Non-Viral Gene Delivery Vectors: The Role of the Chemical and Physical Architecture of Macromolecules.

Gene therapy is the technique of inserting foreign genetic elements into host cells to achieve a therapeutic effect. Although gene therapy was initially formulated as a potential remedy for specific genetic problems, it currently offers solutions for many diseases with varying inheritance patterns and acquired diseases. There are two major groups of vectors for gene therapy: viral vector gene therapy and non-viral vector gene therapy. This review examines the role of a macromolecule's chemical and physical architecture in non-viral gene delivery, including their design and synthesis. Polymers can boost circulation, improve delivery, and control cargo release through various methods. The prominent examples discussed include poly-L-lysine, polyethyleneimine, comb polymers, brush polymers, and star polymers, as well as hydrogels and natural polymers and their modifications. While significant progress has been made, challenges still exist in gene stabilization, targeting specificity, and cellular uptake. Overcoming cytotoxicity, improving delivery efficiency, and utilizing natural polymers and hybrid systems are vital factors for prospects. This comprehensive review provides an illuminating overview of the field, guiding the way toward innovative non-viral-based gene delivery solutions.

A Green Laboratory Approach to Medical Sample Transportation: Assessing the Carbon Dioxide (CO2) Footprint of Medical Sample Transportation by Drone, Combustion Car, and Electric Car

In response to escalating climate change concerns, this study evaluates the ecological impact and efficiency of medical sample transportation using drones, combustion cars, and electric cars across various terrains and weather conditions in Liechtenstein and Switzerland. Through a comparative analysis, we found that combustion cars emit the highest average CO2 at 159.5 g per kilometer (g/km), while electric cars significantly reduce emissions to an average of 3.43 g/km, representing just 2.15% of the emissions from combustion vehicles. Drones emerged as the most environmentally sustainable option, with an average CO2 emission of 0.09 g/km, which is only 0.07% of combustion car emissions and 2.6% of electric car emissions. Drones also demonstrated superior transport efficiency, covering routes that were, on average, 17% shorter in flat terrain and 24% shorter in mountainous regions compared to cars. Additionally, drones achieved substantial time savings, ranging from 13% to 80% faster delivery times depending on the terrain and traffic conditions. These findings highlight the potential of drone technology to revolutionize healthcare logistics by significantly reducing carbon footprints, optimizing transport routes, and improving delivery efficiency. Integrating drones into healthcare transportation networks offers a promising pathway toward a more sustainable and resilient healthcare system.

Research on Fresh Produce Delivery Scheduling Problems under the Perspective of Community E-commerce

This paper addresses the challenges associated with the high costs and logistical difficulties in the distribution of fresh agricultural products from the perspective of community e-commerce. The paper takes the perspective of merchant scheduling and integrates a classical vehicle scheduling model. The study meticulously examines the various costs associated with the distribution process, encompassing fixed costs, transportation costs, refrigeration costs, storage costs and time subsidies. A vehicle routing optimisation model was developed with the dual objectives of cost control and product quality assurance. The use of a genetic algorithm for analysis and solution indicates that this approach can achieve superior cost efficiency and more optimal delivery routes. The results not only confirm the validity of the model and the effectiveness of the solution algorithm, but also provide theoretical underpinnings and viable optimisation strategies for analogous route optimisation challenges. This research has significant reference value and practical relevance for improving delivery efficiency and cost management in community e-commerce.

Advancements in nanomedicine delivery systems: unraveling immune regulation strategies for tumor immunotherapy.

This review highlights the significant role of nanodrug delivery systems (NDDS) in enhancing the efficacy of tumor immunotherapy. Focusing on the integration of NDDS with immune regulation strategies, it explores their transformative impacts on the tumor microenvironment and immune response dynamics. Key advancements include the optimization of drug delivery through NDDS, targeting mechanisms like immune checkpoint blockade and modulating the immunosuppressive tumor environment. Despite the progress, challenges such as limited clinical efficacy and complex manufacturing processes persist. The review emphasizes the need for further research to optimize these systems, potentially revolutionizing cancer treatment by improving delivery efficiency, reducing toxicity and overcoming immune resistance.

Advances in Nanomedicine for Precision Insulin Delivery.

Diabetes mellitus, which comprises a group of metabolic disorders affecting carbohydrate metabolism, is characterized by improper glucose utilization and excessive production, leading to hyperglycemia. The global prevalence of diabetes is rising, with projections indicating it will affect 783.2 million people by 2045. Insulin treatment is crucial, especially for type 1 diabetes, due to the lack of β-cell function. Intensive insulin therapy, involving multiple daily injections or continuous subcutaneous insulin infusion, has proven effective in reducing microvascular complications but poses a higher risk of severe hypoglycemia. Recent advancements in insulin formulations and delivery methods, such as ultra-rapid-acting analogs and inhaled insulin, offer potential benefits in terms of reducing hypoglycemia and improving glycemic control. However, the traditional subcutaneous injection method has drawbacks, including patient compliance issues and associated complications. Nanomedicine presents innovative solutions to these challenges, offering promising avenues for overcoming current drug limitations, enhancing cellular uptake, and improving pharmacokinetics and pharmacodynamics. Various nanocarriers, including liposomes, chitosan, and PLGA, provide protection against enzymatic degradation, improving drug stability and controlled release. These nanocarriers offer unique advantages, ranging from enhanced bioavailability and sustained release to specific targeting capabilities. While oral insulin delivery is being explored for better patient adherence and cost-effectiveness, other nanomedicine-based methods also show promise in improving delivery efficiency and patient outcomes. Safety concerns, including potential toxicity and immunogenicity issues, must be addressed, with the FDA providing guidance for the safe development of nanotechnology-based products. Future directions in nanomedicine will focus on creating next-generation nanocarriers with precise targeting, real-time monitoring, and stimuli-responsive features to optimize diabetes treatment outcomes and patient safety. This review delves into the current state of nanomedicine for insulin delivery, examining various types of nanocarriers and their mechanisms of action, and discussing the challenges and future directions in developing safe and effective nanomedicine-based therapies for diabetes management.

Regulating the Distribution and Accumulation of Charged Molecules by Progressive Electroporation for Improved Intracellular Delivery.

The cell membrane separates the intracellular compartment from the extracellular environment, constraining exogenous molecules to enter the cell. Conventional electroporation typically employs high-voltage and short-duration pulses to facilitate the transmembrane transport of molecules impermeable to the membrane under natural conditions by creating temporary hydrophilic pores on the membrane. Electroporation not only enables the entry of exogenous molecules but also directs the intracellular distribution of the electric field. Recent advancements have markedly enhanced the efficiency of intracellular molecule delivery, achieved through the utilization of microstructures, microelectrodes, and surface modifications. However, little attention is paid to regulating the motion of molecules during and after passing through the membrane to improve delivery efficiency, resulting in an unsatisfactory delivery efficiency and high dose demand. Here, we proposed the strategy of regulating the motion of charged molecules during the delivery process by progressive electroporation (PEP), utilizing modulated electric fields. Efficient delivery of charged molecules with an expanded distribution and increased accumulation by PEP was demonstrated through numerical simulations and experimental results. The dose demand can be reduced by 10-40% depending on the size and charge of the molecules. We confirmed the safety of PEP for intracellular delivery in both short and long terms through cytotoxicity assays and transcriptome analysis. Overall, this work not only reveals the mechanism and effectiveness of PEP-enhanced intracellular delivery of charged molecules but also suggests the potential integration of field manipulation of molecular motion with surface modification techniques for biomedical applications such as cell engineering and sensitive cellular monitoring.

Multi-stage incentive contract design of aviation complex product multi-task delivery strategy

The increasing demand for aviation complex products makes complex product manufacturers pay more attention to delivery efficiency, and the efficiency and effect of delivery problems are the key factors that restrict delivery efficiency. A series of delivery strategy combinations of delivery subjects will affect delivery output and delivery efficiency. This study aims to design a long-term effective incentive contract, which stimulates the subjective initiative of the subject and then investigates the effect of the incentive contract on delivery efficiency under different combinations of delivery strategies. We consider the behavioral characteristics of each technical business department to expand the benchmark incentive model, such as the degree of perceived revenue fairness, the variation of the three relationships (neutrality, competition, and cooperation), and the level of technological transformation capability. The multi-stage incentive mechanism which combines explicit incentives and implicit incentives is developed to explore the optimal delivery strategies based on a benchmark model. The results show that incentive contracts can improve delivery efficiency and benefit delivery centers and technical business departments. The delivery decisions of the department are influenced by the closeness of department relationships and the fairness of assignment, and the departments tend to pay more effort in tasks with high relative importance and low effort cost. When the relative importance of tasks is equal to the ratio of marginal cost, a weak incentive zone in the delivery incentive contract exists. The incentive effect of reputation effect is obvious except for the last stage. Based on the designed incentive contracts, the subjective initiative of the participants can be effectively stimulated to empower complex product delivery.

Research on the Optimization Strategy of Last-Mile Distribution under the E-Commerce Logistics Model

With the rapid development of e-commerce, last-mile delivery, as a key link in e-commerce logistics, is essential to provide efficient and punctual delivery services. This study aims to explore the optimization strategy of last-mile delivery under the e-commerce logistics model to improve delivery efficiency, reduce costs, and provide a better user experience. This study adopts the method of literature review and case analysis, combined with the actual e-commerce logistics operation, to conduct an in-depth study on the problem of last-mile delivery.

New Generation Nebulizers.

Standard nebulizers are intended for general purpose use and typically are continuously operated jet or ultrasonic nebulizers. Evolutionary developments such as breath-enhanced and breath-triggered devices have improved delivery efficiency and ease of use, yet are still suitable for delivery of nebulized medications approved in this category. However, recent developments of vibrating membrane or mesh nebulizers have given rise to a significant increase in delivery efficiency requiring reformulation of former drug products or development of new formulations to match the enhanced delivery characteristics of these new devices. In addition, the electronic nature of the new devices enables tailoring to specific applications and patient groups, such as guiding or facilitating optimal breathing and improving adherence to the therapeutic regimen. Addressing these patient needs leads to new nebulization technologies being embedded in devices with fundamentally distinct functionality, modes of operation and patient interfaces. Therefore, new generation nebulizers can no longer be regarded as one category with fairly similar performance characteristics but must be clinically tested and approved as drug/device combinations together with the specific drug formulation, similar to the approval of pressurized metered-dose inhalers and dry powder inhalers. From a regulatory viewpoint, it is required that drug and device are associated with each other as combinations by clear, mutually conforming labels or, even more desirably, by distinct container-closure systems (closed system nebulizer).

Accelerated infected wound healing by probiotic-based living microneedles with long-acting antibacterial effect

Delays in infected wound healing are usually a result of bacterial infection and local inflammation, which imposes a significant and often underappreciated burden on patients and society. Current therapies for chronic wound infection generally suffer from limited drug permeability and frequent drug administration, owing to the existence of a wound biofilm that acts as a barrier restricting the entry of various antibacterial drugs. Here, we report the design of a biocompatible probiotic-based microneedle (MN) patch that can rapidly deliver beneficial bacteria to wound tissues with improved delivery efficiency. The probiotic is capable of continuously producing antimicrobial substances by metabolizing introduced glycerol, thereby facilitating infected wound healing through long-acting antibacterial and anti-inflammatory effects. Additionally, the beneficial bacteria can remain highly viable (>80 %) inside MNs for as long as 60 days at 4 °C. In a mouse model of Staphylococcus aureus-infected wounds, a single administration of the MN patch exhibited superior antimicrobial efficiency and wound healing performance in comparison with the control groups, indicating great potential for accelerating infected wound closure. Further development of live probiotic-based MN patches may enable patients to better manage chronically infected wounds.

Optimization of Dendritic Polypeptide Delivery System for Antisense Antibacterial Agents Targeting ftsZ.

There is an urgent requirement for a novel treatment strategy for drug-resistant Staphylococcus aureus (S. aureus) infection. Antisense antimicrobials are promising antimicrobials, and efficient drug delivery systems are necessary for the further development of antisense antimicrobials. To develop new antisense drugs and further improve delivery efficiency and safety, we designed and screened new antisense sequences and optimized dendritic polypeptide nanoparticles (DP-AD) discovered in previous studies. The N/P ratio is optimized from 8:1 to 6:1, and the positive charge number of the optimized DP-AD is studied comprehensively. The results show that the N/P ratio and positive charge number have no significant effect on the particle size distribution and transport efficiency of DP-AD. Reducing the N/P ratio can significantly reduce the cytotoxicity of DP-AD, but it does not affect its delivery efficiency and antibacterial activity. However, in drug-resistant strains, the antibacterial activity of DP-AD76:1 with 10 positive charges is higher than that of DP-AD86:1 with 8 positive charges. Our research discovered a novel ASOs targeting ftsZ and concluded that DP-AD76:1 with 10 positive charges was the optimal choice at the current stage, which provided a promising strategy for the treatment of drug-resistant S. aureus.

Supramolecular dye nanoassemblies for advanced diagnostics and therapies.

Dyes have conventionally been used in medicine for staining cells, tissues, and organelles. Since these compounds are also known as photosensitizers (PSs) which exhibit photoresponsivity upon photon illumination, there is a high desire towards formulating these molecules into nanoparticles (NPs) to achieve improved delivery efficiency and enhanced stability for novel imaging and therapeutic applications. Furthermore, it has been shown that some of the photophysical properties of these molecules can be altered upon NP formation thereby playing a major role in the outcome of their application. In this review, we primarily focus on introducing dye categories, their formulation strategies and how these strategies affect their photophysical properties in the context of photothermal and non-photothermal applications. More specifically, the most recent progress showing the potential of dye supramolecular assemblies in modalities such as photoacoustic and fluorescence imaging, photothermal and photodynamic therapies as well as their employment in photoablation as a novel modality will be outlined. Aside from their photophysical activity, we delve shortly into the emerging application of dyes as drug stabilizing agents where these molecules are used together with aggregator molecules to form stable nanoparticles.

The Synthesis of carbon dots//zincoxide (CDs/ZnO-H400) by using hydrothermal methods for degradation of ofloxacin antibiotics and reactive red azo dye (RR141)

The development of photocatalytic powders to remove contaminants from air solutions is an important field of research in the field of environmental conservation. CD/ZnO-H400, a heterogeneous photocatalytic production, is utilized to degrade the reactive red dye and the antibiotic ofloxacin found in wastewater. This study explains the synthesis of carbon dots (CDs) derived from coconut air and zinc oxide (ZnO) using a hydrothermal method at a temperature of 180 °C with a duration of 4 h and subsequently calcinated at a 400 °C temperature for 4 h. This shows a significant improvement in photocatalytic performance due to improved delivery efficiency at the interface. The cost-efficient use of solar energy allows the comprehensive elimination of harmful pollutants through detoxification. The removal of the contaminant takes place through the first-order reaction, with RR141 showing the highest constant rate at 0.03 min−1, while ofloxacin has a constant speed at 0.01 min−1. The photocatalytic stability is measured after five cycles. The study also tested the impact of sunlight on degradation, showing a degrading rate of 98% for RR141 and 96% for ofloxacin. This study displays a new catalyst powder synthesized from carbon dots derived from the air, coconut and ZnO, showing remarkable photoactivity to completely remove harmful dyes and antibiotics from the surrounding environment.

AI in supply chain optimization: A comparative review of USA and African Trends

The integration of Artificial Intelligence (AI) in supply chain management has emerged as a critical driver of efficiency and competitiveness in global markets. This paper provides a comparative review of AI trends in supply chain optimization between the United States and African regions, shedding light on the unique challenges and opportunities faced by each. In the United States, AI adoption in supply chain optimization has been robust, with a focus on predictive analytics, machine learning, and advanced automation technologies. American companies leverage AI to enhance demand forecasting, optimize inventory management, and streamline logistics processes. The integration of AI-driven solutions has allowed U.S. businesses to achieve higher accuracy in demand predictions, reduce lead times, and minimize operational costs. Furthermore, the use of AI algorithms in route optimization has significantly improved delivery efficiency, leading to enhanced customer satisfaction. Contrastingly, African countries are experiencing a more gradual but steadily increasing adoption of AI in supply chain optimization. Limited access to advanced technology infrastructure, coupled with resource constraints, has posed challenges for African businesses. However, innovative approaches are being explored, such as the use of mobile technologies and cloud-based solutions to overcome infrastructure limitations. AI applications in African supply chains focus on improving visibility, minimizing waste, and ensuring timely delivery. The continent's diverse supply chain landscape, encompassing agriculture, mining, and manufacturing, presents a unique set of challenges that AI aims to address. Both the United States and African nations recognize the potential of AI to transform supply chain management. While the U.S. is at the forefront of AI implementation, Africa is forging ahead with tailored solutions that align with its specific context. Collaboration and knowledge exchange between these regions could pave the way for a globalized approach to AI in supply chain optimization. This review underscores the importance of understanding regional nuances in adopting AI technologies, fostering collaboration for mutual benefit, and advancing the global evolution of AI-driven supply chain management.

Copper-Based Nanomedicines for Cuproptosis-Mediated Effective Cancer Treatment.

The recent discovery of cuproptosis, a novel copper-ion-induced cell death pathway, has suggested the novel therapeutic potential for treating heterogeneous and drug-resistant cancers. Currently, copper ionophore-based therapeutics have been designed to treat cancers, utilizing copper ions as a strategic tool to impede tumor proliferation and promote cellular demise. However, limitations of copper ionophore-based therapies include nontargeted delivery of copper ions, low tumor accumulation, and short half-life. Strategies to enhance specificity involve targeting intracellular cuproptosis mechanisms using nanotechnology-based drugs. Additionally, the importance of exploring combination therapies cannot be overstated, as they are a key strategy in improving the efficacy of cancer treatments. Recent studies have reported the anticancer effects of nanomedicines that can induce cuproptosis of cancer both invitro and invivo. These cuproptosis-targeted nanomedicines could improve delivery efficiency with the pharmacokinetic properties of copper ion, resulting in increasing cuproptosis-based anticancer effects. This review will summarize the intricate nexus between copper ion and carcinogenesis, examining the pivotal roles of copper homeostasis and its dysregulation in cancer progression and fatality. Furthermore, we will introduce the latest advances in cuproptosis-targeted nanomedicines for cancer treatment. Finally, the challenges in cuproptosis-based nanomedicines will be discussed for future development directions.

Drone‐Assisted Long‐Distance Delivery of Medical Supplies with Recharging Stations in Rural Communities

In the past few years, drones have been adopted as a novel delivery tool towards medical supplies, improving delivery service efficiency due to fast speed and neglection of geographical limitations. However, the flight endurance of a battery‐operated drone is limited for long‐distance medical supplies delivery operations. Recharging stations, as a kind of drone facility, allow multiple stops for drones to supplement the power to overcome the flight‐range limitations. This paper studies drone‐assisted long‐distance medical supplies delivery with recharging stations in rural communities by a mixed integer linear programming model. To illustrate the applicability of this model and explore the key factors influencing delivery efficiency of medical supplies, a case study from China is conducted. The results indicate that enhancements on the speed of a truck or a drone can yield considerable delivery cost reduction. In addition, drone‐recharging technology advances can improve delivery efficiency of medical supplies in rural communities.

Optimizing Logistics System Monitoring with FIFO Method Using Intelligent System

Efficient and well-organized logistics systems are crucial for maintaining operational smoothness and customer satisfaction. In this research, we delve into the optimization of logistics system monitoring using the First-In, First-Out (FIFO) method based on smart system technology. The FIFO method has become a widely used approach in inventory management and product distribution. However, achieving optimal FIFO implementation can be challenging due to demand fluctuations and changing priorities. In the proposed optimization method, we integrate data analysis and artificial intelligence to enhance the utilization of the FIFO method in logistics system monitoring. This method gathers real-time data on inventory levels, customer demands, and resource availability. Employing intelligent algorithms, the method analyzes data to identify demand trends, predict future inventory needs, and optimize the sequence of product deliveries using the FIFO method. The conducted tests indicate that this optimization method successfully improves delivery efficiency and reduces operational costs within the logistics system. Moreover, the method can adapt to real-time changes in demand and priorities, enhancing flexibility and responsiveness in logistics system monitoring. This research makes a significant contribution to the development of more efficient and intelligent logistics monitoring systems