Embedded System Performance Analysis for Implementing a Portable Drowsiness Detection System for Drivers

Drowsiness on the road is a widespread problem with fatal consequences; thus, a multitude of systems and techniques have been proposed. Among existing methods, Ghoddoosian et al. utilized temporal blinking patterns to detect early signs of drowsiness, but their algorithm was tested only on a powerful desktop computer, which is not practical to apply in a moving vehicle setting. In this paper, we propose an efficient platform to run Ghoddosian's algorithm, detail the performance tests we ran to determine this platform, and explain our threshold optimization logic. After considering the Jetson Nano and Beelink (Mini PC), we concluded that the Mini PC is the most efficient and practical to run our embedded system in a vehicle. To determine this, we ran communication speed tests and evaluated total processing times for inference operations. Based on our experiments, the average total processing time to run the drowsiness detection model was 94.27 ms for Jetson Nano and 22.73 ms for the Beelink (Mini PC). Considering the portability and power efficiency of each device, along with the processing time results, the Beelink (Mini PC) was determined to be most suitable. Also, we propose a threshold optimization algorithm, which determines whether the driver is drowsy or alert based on the trade-off between the sensitivity and specificity of the drowsiness detection model. Our study will serve as a crucial next step for drowsiness detection research and its application in vehicles. Through our experiment, we have determinend a favorable platform that can run drowsiness detection algorithms in real-time and can be used as a foundation to further advance drowsiness detection research. In doing so, we have bridged the gap between an existing embedded system and its actual implementation in vehicles to bring drowsiness technology a step closer to prevalent real-life implementation.Comment: 26 pages, 13 figures, 4 table

Estimation of the Available Rooftop Area for Installing the Rooftop Solar Photovoltaic (PV) System by Analyzing the Building Shadow Using Hillshade Analysis

AbstractFor continuous promotion of the solar PV system in buildings, it is crucial to analyze the rooftop solar PV potential. However, the rooftop solar PV potential in urban areas highly varies depending on the available rooftop area due to the building shadow. In order to estimate the available rooftop area accurately by considering the building shadow, this study proposed an estimation method of the available rooftop area for installing the rooftop solar PV system by analyzing the building shadow using Hillshade Analysis. A case study of Gangnam district in Seoul, South Korea was shown by applying the proposed estimation method

Development of the monthly average daily solar radiation map using A-CBR, FEM, and kriging method

Photovoltaic (PV) system could be implemented to mitigate global warming and lack of energy. To maximize its effectiveness, the monthly average daily solar radiation (MADSR) should be accurately estimated, and then an accurate MADSR map could be developed for final decision-makers. However, there is a limitation in improving the accuracy of the MADSR map due to the lack of weather stations. This is because it is too expensive to measure the actual MADSR data using the remote sensors in all the sites where the PV system would be installed. Thus, this study aimed to develop the MADSR map with improved estimation accuracy using the advanced case-based reasoning (A-CBR), finite element method (FEM), and kriging method. This study was conducted in four steps: (i) data collection; (ii) estimation of the MADSR data in the 54 unmeasured locations using the A-CBR model; (iii) estimation of the MADSR data in the 89 unmeasured locations using the FEM model; and (iv) development of the MADSR map using the kriging method. Compared to the previous MADSR map, the proposed MADSR map was determined to be improved in terms of its estimation accuracy and classification level. First published online: 03 May 201

Treatment of Discoid Lupus Erythematosus in a Dog with Human Intravenous Immunoglobulin

Background: Discoid lupus erythematosus (DLE) is a common canine autoimmune skin disease, in which systemic manifestations are absent. Skin Lesions are usually present on the nasal planum, and characterised by erythema, depigmentation, erosion, ulceration, and crusting. The diagnosis is based on histopathological results, which should demonstrate lymphoplasmacytic lichenoid-interface dermatitis. Human intravenous immunoglobulin (hIVIg) has been used in veterinary medicine to treat cutaneous diseases including erythema multiforme, PF, and severe adverse cutaneous drug reactions. In human medicine, it has been effective to treat DLE. This report firstly describes the clinical response to hIVIg in a dog with DLE resistant to common immunosuppressive drugs.Case: A 5-year-old, intact female Shih Tzu presented with a 1-month history of slowly progressive black crusting on the nasal planum, chin, and claw. Based on the results of a dermatologic examination, superficial pyoderma was diagnosed. The skin lesions did not improve during and after anti-infective treatment. After removing the crusts, a skin biopsy was obtained from the muzzle. Histopathology of lesional skin biopsy specimens revealed lymphoplasmacytic interface dermatitis at the dermoepidermal junction. Microscopic examination also revealed vacuolar changes and pigmentary incontinence of the basal layer as a lichenoid tissue reaction. No mites or fungi were detected on the skin section. The absence of acantholytic cells excluded pemphigus foliaceus, which is also characterised by the lesions of the nasal planum. Based on the distribution of the lesions, histopathology and exclusion of other dermatoses, the dog was diagnosed with DLE. The skin lesions temporarily improved after treatment with prednisolone (2 mg/kg PO q12h). However, after tapering the dose of prednisolone, new black crusts developed on the nasal planum and claw. Although the dog was successively treated with other immunosuppressive drugs, including azathioprine, cyclosporin with dexamethasone, and mycophenolate mofetil, black crusts still remained. Due to the low efficacy of these immunosuppressive drugs, hIVIg was administered at 0.5 g/kg once daily for 4 days, for a total dose of 2 g/kg. During hIVIg administration, the crusted lesions gradually improved. After the hIVIg administration, the dog was treated with prednisolone (1 mg/kg PO q12h). The lesions were almost in complete remission at 21 days after an additional application of prednisolone. The skin lesions did not recur, and the treatment was eventually discontinued after 6 weeks of additional prednisolone application.Discussion: The standard treatment of canine DLE includes glucocorticoids, and second-line immunosuppressive drugs, such as azathioprine and cyclosporine, are usually added in cases resistant to steroids. This case suggests that hIVIg may be beneficial as an adjunctive treatment option for canine DLE, especially when the application of standard immunosuppressive drugs is limited due to adverse effects or low efficacy. There is evidence from several studies that the steroid-sparing effect of hIVIg is significant in human patients. In the current case, the effective dose of prednisolone was reduced to 2 mg/kg/day after hIVIg administration, and prednisolone therapy was finally discontinued completely. The hIVIg appears to lower the daily steroid dose requirement in this dog. Keywords: autoimmune skin disease, discoid lupus erythematosus, canine dermatology, immunosuppressive drug, human intravenous immunoglobulin

Embedded System Performance Analysis for Implementing a Portable Drowsiness Detection System for Drivers

Drowsiness on the road is a widespread problem with fatal consequences; thus, a multitude of systems and techniques have been proposed. Among existing methods, Ghoddoosian et al. utilized temporal blinking patterns to detect early signs of drowsiness, but their algorithm was tested only on a powerful desktop computer, which is not practical to apply in a moving vehicle setting. In this paper, we propose an efficient platform to run Ghoddoosian’s algorithm, detail the performance tests we ran to determine this platform, and explain our threshold optimization logic. After considering the Jetson Nano and Beelink (Mini PC), we concluded that the Mini PC is most efficient and practical to run our embedded system in a vehicle. To determine this, we ran communication speed tests and evaluated total processing times for inference operations. Based on our experiments, the average total processing time to run the drowsiness detection model was 94.27 ms for the Jetson Nano and 22.73 ms for the Beelink (Mini PC). Considering the portability and power efficiency of each device, along with the processing time results, the Beelink (Mini PC) was determined to be most suitable. Additionally, we propose a threshold optimization algorithm, which determines whether the driver is drowsy, or alert based on the trade-off between the sensitivity and specificity of the drowsiness detection model. Our study will serve as a crucial next step for drowsiness detection research and its application in vehicles. Through our experiments, we have determined a favorable platform that can run drowsiness detection algorithms in real-time and can be used as a foundation to further advance drowsiness detection research. In doing so, we have bridged the gap between an existing embedded system and its actual implementation in vehicles to bring drowsiness technology a step closer to prevalent real-life implementation

Wheelchair motion control guide using eye gaze and blinks based on bug 2 algorithm

In this work, we propose a new approach alongside the typical method, to control the motorized wheelchair using EOG signals. The new approach grants the user to look around without restraint, while the wheelchair navigates automatically to the desired goal point. Only EOG signals are used to control the wheelchair; eye gazing and blinking. The user can still appoint to control the wheelchair using the typical manual method in case the surroundings and obstacle structures do not assist with the new developed auto navigation method. In the new auto navigation approach the microcontroller can attain the goal point direction and distance by calculating the gaze angle of the user. Bug2 algorithm is utilized to navigate the wheelchair in the auto controlling method. Experimental tests show slightly different results than theory, because the bug algorithms cannot continuously update the robot's position data in experiments

An Environmental and Economic Assessment for Selecting the Optimal Ground Heat Exchanger by Considering the Entering Water Temperature

In order to solve environmental problems such as global warming and resource depletion in the construction industry, interest in new renewable energy (NRE) systems has increased. The ground source heat pump (GSHP) system is the most efficient system among NRE systems. However, since the initial investment cost of the GSHP is quite expensive, a feasibility study needs to be conducted from the life-cycle perspective. Meanwhile, the efficiency of GSHP depends most significantly on the entering water temperature (EWT) of the ground heat exchanger (GHE). Therefore, this study aims to assess the environmental and economic effects of the use of GHE for selecting the optimal GHE. This study was conducted in three steps: (i) establishing the basic information and selecting key factors affecting GHE performances; (ii) making possible alternatives of the GHE installation by considering EWT; and (iii) using life-cycle assessment and life-cycle cost, as well as comprehensive evaluation of the environmental and economic effects on the GHE. These techniques allow for easy and accurate determination of the optimal design of the GHE from the environmental and economic effects in the early design phase. In future research, a multi-objective decision support model for the GSHP will be developed

Economic and Environmental Evaluation Model for Selecting the Optimum Design of Green Roof Systems in Elementary Schools

Green-roof systems offer various benefits to man and nature, such as establishing ecological environments, improving landscape and air quality, and offering pleasant living environments. This study aimed to develop an optimal-scenario selection model that considers both the economic and the environmental effect in applying GRSs to educational facilities. The following process was carried out: (i) 15 GRSs scenarios were established by combining three soil and five plant types and (ii) the results of the life cycle CO₂ analyses with the GRSs scenarios were converted to an economic value using certified emission reductions (CERs) carbon credits. Life cycle cost (LCC) analyses were performed based on these results. The results showed that when considering only the currently realized economic value, the conventional roof system is superior to the GRSs. However, the LCC analysis that included the environmental value, revealed that compared to the conventional roof system, the following six GRSs scenarios are superior (cost reduction; reduction ratio; in descending order): scenarios 13 ($195,229; 11.03 ($188,178; 10.6%), 8 ($181,558; 10.3$130,464; 7.4%), 2 ($124,566; 7.0$113,931; 6.4%). Although the effect is relatively small in terms of cost reduction, environmental value attributes cannot be ignored in terms of the reduction ratio