Strengthening Active Aging through Older People’s Association and Economic Activity of the Older People in Nepal

Aging is a natural lifelong process ending in death. Many older people are living in poverty. Older people are generally considered dependent on others as they grow older. The purpose of this article is to explore the entrepreneurship activities of Nepalese older adults. Data for this study were collected from the project Help Age International (HAI) implemented in Nepal. Qualitative data observations and interviews were used to collect data. The findings of this study show the formation of the Older People’s Association (OPA) has supported many older people to participate outside the home in various social activities. Moreover, regular deposits through OPAs offer little help. OPAs support older people in their need of financial support to implement minor entrepreneurship. Older people who received support were pleased and were actively involved in their activities and also regularly deposited money in them. Subsequently, older people’s participation in social activities has increased and also helped to lower elderly abuse, loneliness, and depression. Local governments should promote such activities which will help with healthy aging.

Efficient People Detection with Infrared Images

This work focuses on the problem of monitoring the coastline, which in Portugal’s case means monitoring 3007 kilometers, including 1793 maritime borders with the Atlantic Ocean to the south and west. The human burden on the coast becomes a problem, both because erosion makes the cliffs unstable and because pollution increases, making the fragile dune ecosystem difficult to preserve. It is becoming necessary to increase the control of access to beaches, even if it is not a popular measure for internal and external tourism. The methodology described can also be used to monitor maritime borders. The use of images acquired in the infrared range guarantees active surveillance both day and night, the main objective being to mimic the infrared cameras already installed in some critical areas along the coastline. Using a series of infrared photographs taken at low angles with a modified camera and appropriate filter, a recent deep learning algorithm with the right training can simultaneously detect and count whole people at close range and people almost completely submerged in the water, including partially visible targets, achieving a performance with F1 score of 0.945, with 97% of targets correctly identified. This implementation is possible with ordinary laptop computers and could contribute to more frequent and more extensive coverage in beach/border surveillance, using infrared cameras at regular intervals. It can be partially automated to send alerts to the authorities and/or the nearest lifeguards, thus increasing monitoring without relying on human resources.

Towards complex scenes: A deep learning-based camouflaged people detection method for snapshot multispectral images

Camouflaged people are extremely expert in actively concealing themselves by effectively utilizing cover and the surrounding environment. Despite advancements in optical detection capabilities through imaging systems, including spectral, polarization, and infrared technologies, there is still a lack of effective real-time method for accurately detecting small-size and high-efficient camouflaged people in complex real-world scenes. Here, this study proposes a snapshot multispectral image-based camouflaged detection model, multispectral YOLO(MS-YOLO), which utilizes the SPD-Conv and Sim AM modules to effectively represent targets and suppress background interference by exploiting the spatial-spectral target information. Besides, the study constructs the first real-shot multispectral camouflaged people dataset(MSCPD), which encompasses diverse scenes, target scales, and attitudes. To minimize information redundancy, MS-YOLO selects an optimal subset of 12 bands with strong feature representation and minimal inter-band correlation as input. Through experiments on the MSCPD, MS-YOLO achieves a mean Average Precision of 94.31% and real-time detection at 65 frames per second, which confirms the effectiveness and efficiency of our method in detecting camouflaged people in various typical desert and forest scenes. Our approach offers valuable support to improve the perception capabilities of unmanned aerial vehicles in detecting enemy forces and rescuing personnel in battlefield.

Alcohol and illicit drugs:prevalence of alcohol and illicit drug use and their predictors in young people from Argentina,Bulgaria,Chile and Romania

Background:Alcohol and illicit drugs(AID)continue to be a major global health concern.Although preventable,AID is linked to millions of deaths annually worldwide.The situation is particularly grave for young people,with AID being a major direct risk factor for disability-adjusted youth life-years lost and death.It further contributes to assaults,road crashes,accidental poisoning,and suicide,leading to long-term issues and public health concerns.Objective:This study aimed at disclosing current AID prevalence data for Argentinian,Bulgarian,Chilean and Romanian youth.It shed light on the predictors of AID in young people from those countries.Method:The study used an online survey to gather data from people aged 18 to 25(n=1,297).The survey was underpinned by the theory of planned behaviour(TPB).Predictors were investigated separately for drinking alcohol and using illicit drugs.Results:Our data revealed that across the four target countries,49%to 90%of the participants drank alcohol,and 8%to 35%used illicit drugs in the past three months.Between 20%and 91%of them intended to drink,and between 8%and 31%intended to use illicit drugs in the following three months.Our TPB model predicted statistically significant(P<0.001)amounts of variance in drinking alcohol(between 61%and 72%)and using illicit drugs(between 20.3%and 74.4%).Intention was consistent in significantly predicting both behaviours.Evidence around the predictive validity of self-efficacy,age and gender was mixed across the investigated countries.Conclusion:This research provided an update on the scarce AID epidemiological data.It also supplied evidence about what theoretically-informed measures might be useful targets of interventions in the case of Argentina,Bulgaria,Chile and Romania.This new knowledge of understanding substance abuse determinants and prevalence may help researchers and practitioners better meet young people's health prevention needs.

Associations of PNPLA3 and LEP genetic polymorphisms with metabolic-associated fatty liver disease in Thai people living with human immunodeficiency virus

BACKGROUND The prevalence of metabolic-associated fatty liver disease(MAFLD)is a growing public health issue in people living with human immunodeficiency virus(PLWH).However,the pathophysiology of MAFLD is still unknown,and the role of genetic variables is only now becoming evident.AIM To evaluate the associations of gene-polymorphism-related MAFLD in PLWH.METHODS The study employed transient elastography with a controlled attenuation parameter≥248 dB/m to identify MAFLD in patients from a Super Tertiary Hospital in central Thailand.Candidate single-nucleotide polymorphisms(SNPs)were genotyped using TaqMan®MGB probe 5'nuclease assays for seven MAFLD-related genes.Statistical analyses included SNP frequency analysis,Fisher's Exact and Chi-square tests,odds ratio calculations,and multivariable logistic regression.RESULTS The G-allele carriers of PNPLA3(rs738409)exhibited a two-fold rise in MAFLD,increasing by 2.5 times in MAFLD with human immunodeficiency virus infection.The clinical features and genetic patterns imply that LEP rs7799039 A-allele carriers had a nine times(P=0.001)more significant chance of developing aberrant triglyceride among PLWH.CONCLUSION The current study shows an association between PNPLA3 rs738409 and LEP rs7799039 with MAFLD in PLWH.

Hepatitis C virus eradication in people living with human immunodeficiency virus:Where are we now?

Hepatitis C virus(HCV)/human immunodeficiency virus(HIV)co-infection still involves 2.3 million patients worldwide of the estimated 37.7 million living with HIV,according to World Health Organization.People living with HIV(PLWH)are six times greater affected by HCV,compared to HIV negative ones;the greater prevalence is encountered among people who inject drugs and men who have sex with men:the risk of HCV transmission through sexual contact in this setting can be increased by HIV infection.These patients experience a high rate of chronic hepatitis,which if left untreated progresses to end-stage liver disease and hepato-cellular carcinoma(HCC)HIV infection increases the risk of mother to child vertical transmission of HCV.No vaccination against both infections is still available.There is an interplay between HIV and HCV infections.Treatment of HCV is nowadays based on direct acting antivirals(DAAs),HCV treatment plays a key role in limiting the progression of liver disease and reducing the risk of HCC development in mono-and coinfected individuals,especially when used at an early stage of fibrosis,reducing liver disease mortality and morbidity.Since the sustained virological response at week 12 rates were observed in PLWH after HCV eradication,the AASLD has revised its simplified HCV treatment algorithm to also include individuals living with HIV.HCV eradication can determine dyslipidemia,since HCV promotes changes in serum lipid profiles and may influence lipid metabolism.In addition to these apparent detrimental effects on the lipid profile,the efficacy of DAA in HCV/HIV patients needs to be considered in light of its effects on glucose metabolism mediated by improvements in liver function.The aim of the present editorial is to describe the advancement in HCV treatment among PLWH.

Assessing Barriers to Mental Healthcare Interventions for Deaf People in Ghana

While mental health issues are increasingly gaining attention in Ghana, little is known about the situation among deaf people. This study assessed the mental health care needs of deaf people in Ghana. A descriptive design, consisting of interviews and focus group discussions, was used to collect data from 97 participants. Findings indicated that participants had limited knowledge on mental health issues. Mental health stigma, inaccessible mental health information and exclusion from mental health programmes were the major barriers hindering access to mental health care services. This study bridges the knowledge gap and provides evidence for the implementation of deaf-friendly services.

Practice of Barrier Measures against COVID-19 Among Diabetic People Followed at Departmental University Hospital Center Ouémé-Plateau, Benin, in 2021

Introduction: COVID-19 is a pandemic disease caused by the coronavirus SARS-COV2 appeared in China in 2019. The aim of the study was to evaluate the practice of barrier measures against COVID-19 and to identify associated factors among diabetics followed at Departmental University Hospital Center Ouémé-Plateau, Benin, in 2021. Methods: This was a cross-sectional study conducted from June to August 2021, including diabetics aged 18 and over, hospitalized or received for medical visits in the department of medicine at the target hospital. Data were collected during an interview with each participant thanks to a questionnaire. “Good practice” was defined as regular practice of at least two of three barrier measures: hand washing, physical distancing and mask-wearing. Results: A total of 110 diabetics were included with a female predominance (55.5%) and a mean age of 57 ± 11.3 years. Among them, 89.1% washed their hands, 41.8% respected physical distancing and 12.7% wore a mask. The proportion of good practice was 47.3%. Only 5 practiced the three barrier measures. Only age group was associated with good practice. Conclusion: The study showed a low proportion of good practice of barrier measures against COVID-19 among diabetic people surveyed. It is important to continue the action for COVID-19 prevention among diabetic people in the targeted hospital and in other hospitals in Benin.

Understanding Behavioral Manifestations of Obsessive-Compulsive Disorder in People with Intellectual Disabilities—A Qualitative Study

Background: There is limited knowledge about obsessive-compulsive disorder (OCD) in people with intellectual disabilities (IDs). This paper describes the manifestation of compulsive behaviors associated with OCD at the behavioral level in people with ID in institutionalized settings. The aim was to gain nuanced insight into appropriate understanding and classification in this specific context, and derive implications for research and practice. Methods: Individual cases of people with ID (n = 7) were studied to assess compulsive symptoms through two days of on-site observation of the person with ID within the institution, guided group discussions (n = 28), and semi-structured interviews with key informants and caregivers of the person with ID (n = 20). Caregiver ratings of the compulsive behavior checklist were compiled. Data were analyzed using qualitative content analysis. Results: All forms of OCD were present. Characteristics of compulsive behaviors in people with ID at the behavioral level included less complex and more obvious compulsive acts, immediate responses, signs of tension, motor restlessness, facial expression changes, repetition, need for predictability, time-consuming behaviors, and aggressive reactions when these acts were interrupted. Some of the compulsive behaviors corresponded to the ICD-11 OCD code 6B20, and others to compulsions as a psychological symptom (MB23.4). Conclusions: OCD may manifest atypically at the behavioral level in people with ID, posing significant challenges for accurate classification due to symptom ambiguity. Follow-up differential diagnostic studies are needed to more accurately identify and differentiate OCD symptoms in people with ID. Further, disorder-specific guidelines for recognizing OCD in people with ID are needed for institutionalized settings without psychiatric-psychotherapeutic expertise.

Narrative Empathy and Patriotism--An Analysis of the Chinese“Main-Melody”Film My People,My Country

Narrative empathy is a relatively new theory and it can guide researchers in the studies of main-melody films so as to promote the communication of the core values of the society.The rhetorical mechanism of narrative empathy can be illustrated from five rhetorical elements,including rhetor,rhetorical goal,rhetorical situation,rhetorical strategy and audience.The theory of narrative empathy can be applied to the case study of the film My People,My Country.In the production of this film,the directors are the rhetors.The rhetors uphold the tenet of closeness,choose the right rhetorical situation as the 70th birthday of the People’s Republic of China,and use appropriate rhetorical strategies in order to realize the rhetorical goals of evoking empathy and inspiring patriotic feelings in the audience’s minds.An exploration and application of narrative empathy can be conducive to the empathic communication of Chinese main-melody films in order to achieve better communication effect.

People's Well-rounded Development:The Value Orientation of Common Prosperity in the New Era

Achieving common prosperity for all is an important feature of Chinese modernization and an essential requirement of socialism with Chinese characteristics,with the core value orientation of promoting the people’s well-rounded development.This reflects the close relationship between people’s well-rounded development and common prosperity and implies that common prosperity is not just an economic issue,but also a political matter,a moral subject,and a human rights goal.Being“people-centered”is the core positioning of common prosperity,with its inherent collective and individual attributes.In terms of the object dimension of prosperity,it encompasses a wide range of rights such as material and spiritual well-being,which are advanced in a coordinated manner,and a deepening level of guarantee gradually improving.In the practical concept of“shared development,”it emphasizes the unity of state obligations and individual responsibilities,as well as the phased approach and promotion of common prosperity through the rule of law.Therefore,the essence of common prosperity lies in shifting from a“material-centered”perspective to a“people’s well-rounded development-centered”perspective.It combines the principles of fairness and inclusiveness with the recognition of diverse developmental needs.The focus is on enhancing the subjective initiative of the people,aiming to truly achieve the happiness of the people and promote people’s well-rounded development through the realization of“common prosperity.”

The Psychosomatic Traits of“People with the Five Elements in Traditional Chinese Medicine”:A Qualitative Study

Objective To identify the representative attributes of the five elements of a person with a qualitative methodology and provide the basis for the clinical diagnosis and treatment of“people with the five elements in traditional Chinese medicine(TCM).”Methods Data collected from the literature review,two sessions of brainstorming of experts with related experience in“people with the five elements in TCM”from October 2020 to December 2020,and six rounds of in-depth interviews with 30 participants who had various attributes of the five elements from March 2021 to October 2021 were analyzed.Triangulation was used in this study,and theming and synthesizing were used to analyze the data.Results A total of 31 experts and 30 interviewees participated in this study.The median age of the experts and interviewees were 48.0 and 38.5 years,respectively;51.66%and 54.8%of experts and interviewees,respectively,were men.The descriptors of facial diagrams of“people with the five elements in TCM”were complexion,shape,distribution state of facial bones,convergence trend of facial muscles,and facial expression.A theoretical model of“people with the five elements in TCM”was shaped based on these findings.Conclusion The study suggests a possibility for bridging the gap between personality and bodily state,identifying an avenue for personality research from the perspective of TCM.

Smart Shoes Safety System for the Blind People Based on (IoT) Technology

People’s lives have become easier and simpler as technology has proliferated.This is especially true with the Internet of Things(IoT).The biggest problem for blind people is figuring out how to get where they want to go.People with good eyesight need to help these people.Smart shoes are a technique that helps blind people find their way when they walk.So,a special shoe has been made to help blind people walk safely without worrying about running into other people or solid objects.In this research,we are making a new safety system and a smart shoe for blind people.The system is based on Internet of Things(IoT)technology and uses three ultrasonic sensors to allow users to hear and react to barriers.It has ultrasonic sensors and a microprocessor that can tell how far away something is and if there are any obstacles.Water and flame sensors were used,and a sound was used to let the person know if an obstacle was near him.The sensors use Global Positioning System(GPS)technology to detect motion from almost every side to keep an eye on them and ensure they are safe.To test our proposal,we gave a questionnaire to 100 people.The questionnaire has eleven questions,and 99.1%of the people who filled it out said that the product meets their needs.

Efficient Body-Transfer Wheelchair for Assisting Functionally Impaired People

Functionally impaired people always have difficulty accomplishing activities of daily living.In this regard,tasks including toileting and bathing have a higher prevalence rate of injuries and greater risk of falling.In this study,a body-transfer wheelchair was developed to assist people in transferring from bed to wheelchair for bathing,and toileting.The bodytransfer wheelchair is a semi-automatic wheelchair that has features such as a controlled leg and backrest,linkage commode slot,and height adjustment.The wheelchair consists of a seat and a main frame that can be detached to enable bathtub transfer.This mechanism lets the user stay on the seat while being transferred into the bathtub without any risk of falling.A linkage mechanism was developed as a part of the seat for ease of toileting.Kinematic and force analysis was conducted to calculate the force required for each actuator.It has been proved by the experimental results that the wheelchair can securely and comfortably transfer a patient from the bed to the toilet or bathtub.A survey has been conducted to evaluate the wheelchair prototype design idea.Two focus groups were chosen:one comprised of functionally impaired people,and the other comprised of caregivers.The results of the survey show that 60%of both functionally impaired people and caregivers would like to use the body-transfer wheelchair for toileting and bathing purpose.Additionally,on average 65%of both focus groups find it convenient to operate the body-transfer wheelchair independently.

Deep Transfer Learning-Enabled Activity Identification and Fall Detection for Disabled People

The human motion data collected using wearables like smartwatches can be used for activity recognition and emergency event detection.This is especially applicable in the case of elderly or disabled people who live self-reliantly in their homes.These sensors produce a huge volume of physical activity data that necessitates real-time recognition,especially during emergencies.Falling is one of the most important problems confronted by older people and people with movement disabilities.Numerous previous techniques were introduced and a few used webcam to monitor the activity of elderly or disabled people.But,the costs incurred upon installation and operation are high,whereas the technology is relevant only for indoor environments.Currently,commercial wearables use a wireless emergency transmitter that produces a number of false alarms and restricts a user’s movements.Against this background,the current study develops an Improved WhaleOptimizationwithDeep Learning-Enabled Fall Detection for Disabled People(IWODL-FDDP)model.The presented IWODL-FDDP model aims to identify the fall events to assist disabled people.The presented IWODLFDDP model applies an image filtering approach to pre-process the image.Besides,the EfficientNet-B0 model is utilized to generate valuable feature vector sets.Next,the Bidirectional Long Short Term Memory(BiLSTM)model is used for the recognition and classification of fall events.Finally,the IWO method is leveraged to fine-tune the hyperparameters related to the BiLSTM method,which shows the novelty of the work.The experimental analysis outcomes established the superior performance of the proposed IWODL-FDDP method with a maximum accuracy of 97.02%.

Effectiveness and safety of subthreshold vibration over suprathreshold vibration in treatment of muscle fatigue in elderly people

Muscle fatigue is common in many populations,particularly elderlies.Aging increases the incidence of muscle fatigue and delays its recovery.There is a huge debate about the current treatments for muscle fatigue,particularly in elderlies.Recently,it has been discovered that mechanoreceptors have an important role as a sensory system in sensing muscle fatigue which could enhance the body's response to muscle fatigue.The function of mechanoreceptors could be enhanced by applying either suprathreshold or subthreshold vibration.Although suprathreshold vibration improves muscle fatigue,it can cause desensitization of cutaneous receptors,discomfort,and paresthesia,which are barriers to clinical use.Subthreshold vibration has been approved as a safe and effective method of training for mechanoreceptors;however,its use and effectiveness in muscle fatigue have never been tested or explained.Possible physiological effects of subthreshold vibration in the treatment of muscle fatigue include:(1)Enhancing the function of mechanoreceptors themselves;(2)Increasing the firing rate and function of alpha motor neurons;(3)Increasing blood flow to fatigued muscles;(4)Decreasing the rate of muscle cell death in elderlies(sarcopenia);and(5)Driving motor commands and allow better performance of muscles to decrease fatigue incidence.In conclusion,the use of subthreshold vibration could be a safe and effective treatment for muscle fatigue in elderlies.It could enhance recovery from muscle fatigue.Finally,Subthreshold Vibration is safe and effective in treating muscle fatigue in comparison to suprathreshold vibration.

Red Deer Optimization with Artificial Intelligence Enabled Image Captioning System for Visually Impaired People

The problem of producing a natural language description of an image for describing the visual content has gained more attention in natural language processing(NLP)and computer vision(CV).It can be driven by applications like image retrieval or indexing,virtual assistants,image understanding,and support of visually impaired people(VIP).Though the VIP uses other senses,touch and hearing,for recognizing objects and events,the quality of life of those persons is lower than the standard level.Automatic Image captioning generates captions that will be read loudly to the VIP,thereby realizing matters happening around them.This article introduces a Red Deer Optimization with Artificial Intelligence Enabled Image Captioning System(RDOAI-ICS)for Visually Impaired People.The presented RDOAI-ICS technique aids in generating image captions for VIPs.The presented RDOAIICS technique utilizes a neural architectural search network(NASNet)model to produce image representations.Besides,the RDOAI-ICS technique uses the radial basis function neural network(RBFNN)method to generate a textual description.To enhance the performance of the RDOAI-ICS method,the parameter optimization process takes place using the RDO algorithm for NasNet and the butterfly optimization algorithm(BOA)for the RBFNN model,showing the novelty of the work.The experimental evaluation of the RDOAI-ICS method can be tested using a benchmark dataset.The outcomes show the enhancements of the RDOAI-ICS method over other recent Image captioning approaches.

Endoscopy demand among county people in southeast China:A cross-sectional study

Objective The popularization of gastroenteroscopy and the introduction of comfortable medical care have further promoted the growth of people's demand,especially the demand for painless endoscopy.This cross-sectional study aims to investigate the current situation and change in county people's demand for endoscopy to promote the development of endoscopy centers in county hospitals in southeast China.Methods From October to December 2021,patients and their family members who came to the Gastroenterology Department in Suichang County People's Hospital of Zhejiang Province were randomly selected to complete the questionnaire.A total of 838 valid questionnaires were collected.Additionally,the original software data of the Endoscopy Center were sampled and retrieved(from October to December every year from 2018 to 2021)for statistical analysis of real-world data.Those who would choose painless endoscopy the next time in the valid questionnaires were included in the painless endoscopy group,while those who would choose ordinary endoscopy the next time were included in the ordinary endoscopy group.Results The stepwise forward binary logistic regression model analysis showed that,patients with“secondhand smoke exposure”were more willing to choose painless endoscopy(OR=1.459,95%CI:1.050-2.028,p=0.025).However,patients with an education level of“primary and below”and“junior high school”,and patients who are suffering from“currently experiencing abdominal distension”,were more willing to choose ordinary endoscopy(OR=0.270,95%CI:0.149-0.488,p<0.001;OR=0.528,95%CI:0.330-0.845,p=0.008;OR=0.536,95%CI:0.334-0.861,p=0.010).Patients with previous experience in painless endoscopy tended to choose painless endoscopy the next time,while patients with previous experience in ordinary endoscopy tended to choose ordinary endoscopy the next time(χ^(2)=140.97,p<0.001).From 2018 to 2021,the proportion of painless endoscopy has increased yearly(p<0.001).Most patients indicated that they would“regularly review gastroenteroscopy”(477/838,56.9%).Conclusions With Suichang County of Zhejiang Province as the representative,the demand for painless endoscopy for people's gastrointestinal cancer detection in southeast China has been increasing yearly.The development of endoscopy centers in county-level hospitals can basically meet the demand growth.Meanwhile,advanced concepts such as comfortable medical care and regular follow-up are gradually popularized at the grassroots level in southeast China.

Intelligent Deep Convolutional Neural Network Based Object DetectionModel for Visually Challenged People

Artificial Intelligence(AI)and Computer Vision(CV)advancements have led to many useful methodologies in recent years,particularly to help visually-challenged people.Object detection includes a variety of challenges,for example,handlingmultiple class images,images that get augmented when captured by a camera and so on.The test images include all these variants as well.These detection models alert them about their surroundings when they want to walk independently.This study compares four CNN-based pre-trainedmodels:ResidualNetwork(ResNet-50),Inception v3,DenseConvolutional Network(DenseNet-121),and SqueezeNet,predominantly used in image recognition applications.Based on the analysis performed on these test images,the study infers that Inception V3 outperformed other pre-trained models in terms of accuracy and speed.To further improve the performance of the Inception v3 model,the thermal exchange optimization(TEO)algorithm is applied to tune the hyperparameters(number of epochs,batch size,and learning rate)showing the novelty of the work.Better accuracy was achieved owing to the inclusion of an auxiliary classifier as a regularizer,hyperparameter optimizer,and factorization approach.Additionally,Inception V3 can handle images of different sizes.This makes Inception V3 the optimum model for assisting visually challenged people in real-world communication when integrated with Internet of Things(IoT)-based devices.

IoT-Driven Optimal Lightweight RetinaNet-Based Object Detection for Visually Impaired People

Visual impairment is one of the major problems among people of all age groups across the globe.Visually Impaired Persons(VIPs)require help from others to carry out their day-to-day tasks.Since they experience several problems in their daily lives,technical intervention can help them resolve the challenges.In this background,an automatic object detection tool is the need of the hour to empower VIPs with safe navigation.The recent advances in the Internet of Things(IoT)and Deep Learning(DL)techniques make it possible.The current study proposes IoT-assisted Transient Search Optimization with a Lightweight RetinaNetbased object detection(TSOLWR-ODVIP)model to help VIPs.The primary aim of the presented TSOLWR-ODVIP technique is to identify different objects surrounding VIPs and to convey the information via audio message to them.For data acquisition,IoT devices are used in this study.Then,the Lightweight RetinaNet(LWR)model is applied to detect objects accurately.Next,the TSO algorithm is employed for fine-tuning the hyperparameters involved in the LWR model.Finally,the Long Short-Term Memory(LSTM)model is exploited for classifying objects.The performance of the proposed TSOLWR-ODVIP technique was evaluated using a set of objects,and the results were examined under distinct aspects.The comparison study outcomes confirmed that the TSOLWR-ODVIP model could effectually detect and classify the objects,enhancing the quality of life of VIPs.