Low-cost Smartphone Research Articles

Supporting mobility-aware computational offloading in mobile cloud environment

Mobile Cloud Computing (MCC) enables resource-constrained smartphones to run high processing and storage intensive applications through public clouds or cloudlet code offloading. However, handover support in the MCC context has not been thoroughly explored, since most works do not address the devices mobility during the offloading operation. This paper presents the Mobile Offloading System (MOSys), which supports seamless offloading operations during user mobility between wireless networks. To this end, MOSys benefits from the software-defined networking (SDN) paradigm for mobility management and remote caching techniques to reduce the offloading response time. Also, middleware is responsible for ensuring code and data offloading, profiling service, cloud discovery and application deployment. To evaluate the proposed system and to analyze mobility impact on the offloading performance, several experiments were conducted using different smartphones categories and benchmark applications, on three scenarios. Our results have shown that the MOSys’ mobility management application is energy efficient, especially considering the low-cost smartphone category, while remote caching proved to be an attractive alternative for reducing the offloading response time.

Low cost smart phone diagnostics for food using paper-based colorimetric sensor arrays

There is a need for an accurate end-of-life indicator for packaged food (meat, seafood, dairy food etc.) beyond a simple “best use by” date on the food package. In this work, we propose a low cost solution by repurposing the food’s barcode as a colorimetric sensor array to monitor food condition. A smart phone camera is used to read color information from the sensor barcode for quantitative estimate of the food aging and quality. The sensor is based on cross-reactive vapor sensitive dyes encapsulated in resin microbeads, which are impregnated onto a low cost paper substrate in a barcode pattern. The entire sensor platform is validated by accurately monitoring chicken aging and eventual spoilage under different temperature conditions. The proposed food diagnostics platform has the potential to reduce food waste and eliminate food-borne illness.

Portable neonatal EEG monitoring and sonification on an Android device.

Clinical evaluation of electroencephalogram (EEG) is important for understanding and monitoring the electrical activity present in the brain. In collusion with engineering advances, the movement towards portable, rapid and low-cost EEG monitoring is growing. This will allow a greater availability of monitoring technologies for assessing brain function and health in disadvantaged communities. This paper presents an alternative method for interpreting neonatal brain health in real-time via the sonification of EEG on a smartphone. The paper discusses the implementation of the real-time EEG sonification using a phase vocoder and shows how the method is achievable using low-cost smartphone technologies with energy efficient algorithms.

Tomographic Particle Image Velocimetry using Smartphones and Colored Shadows

We demonstrate the viability of using four low-cost smartphone cameras to perform Tomographic PIV. We use colored shadows to imprint two or three different time-steps on the same image. The back-lighting is accomplished with three sets of differently-colored pulsed LEDs. Each set of Red, Green & Blue LEDs is shone on a diffuser screen facing each of the cameras. We thereby record the RGB-colored shadows of opaque suspended particles, rather than the conventionally used scattered light. We subsequently separate the RGB color channels, to represent the separate times, with preprocessing to minimize noise and cross-talk. We use commercially available Tomo-PIV software for the calibration, 3-D particle reconstruction and particle-field correlations, to obtain all three velocity components in a volume. Acceleration estimations can be done thanks to the triple pulse illumination. Our test flow is a vortex ring produced by forcing flow through a circular orifice, using a flexible membrane, which is driven by a pressurized air pulse. Our system is compared to a commercial stereoscopic PIV system for error estimations. We believe this proof of concept experiment will make this technique available for education, industry and scientists for a fraction of the hardware cost needed for traditional Tomo-PIV.

Growth of E-commerce in India: An Analytical Review of Literature

E-commerce is one of the fastest growing segments in the Indian Economy. Though marked by high growth rate, the Indian e-commerce industry has been behind its counterparts in many developed and emerging economies, primarily due to a relatively low internet user base. In a study conducted by global management consultancy firm AT Kearney in 2015, there were only 39 million online buyers in India; a tiny fraction of the 1.2 billion who live in the country. However, increased technological proliferation combined with internet and mobile penetration, presents a favorable ecosystem for the development of e-commerce in India. The country is currently at the cusp of a digital revolution. Launch of 4G services and decline in the tariffs of data plans and prices of data cards/USB dongles have reduced the cost of ownership of an effective internet connection. Availability of low cost smart phones and the extension of internet and broadband to the remotest corners will boost the augmentation of the internet user base, effectively bridging the gap between potential online buyers and actual buyers. The demographic dividend of the country also seems to encourage and favor the growth of E-commerce. The survival of the e-commerce firms in a highly dynamic environment becomes a challenging task when coupled with the cutthroat competition prevailing in the sector. The onus then lies on the firms to constantly adapt and innovate while providing an information rich and seamless experience to ensure customer loyalty. This study attempts to explore the evolution of e-commerce in India and identifies various challenges to as well the factors responsible for the future growth and development of e commerce.

A Vehicle Steering Recognition System Based on Low-Cost Smartphone Sensors.

Recognizing how a vehicle is steered and then alerting drivers in real time is of utmost importance to the vehicle and driver’s safety, since fatal accidents are often caused by dangerous vehicle maneuvers, such as rapid turns, fast lane-changes, etc. Existing solutions using video or in-vehicle sensors have been employed to identify dangerous vehicle maneuvers, but these methods are subject to the effects of the environmental elements or the hardware is very costly. In the mobile computing era, smartphones have become key tools to develop innovative mobile context-aware systems. In this paper, we present a recognition system for dangerous vehicle steering based on the low-cost sensors found in a smartphone: i.e., the gyroscope and the accelerometer. To identify vehicle steering maneuvers, we focus on the vehicle’s angular velocity, which is characterized by gyroscope data from a smartphone mounted in the vehicle. Three steering maneuvers including turns, lane-changes and U-turns are defined, and a vehicle angular velocity matching algorithm based on Fast Dynamic Time Warping (FastDTW) is adopted to recognize the vehicle steering. The results of extensive experiments show that the average accuracy rate of the presented recognition reaches 95%, which implies that the proposed smartphone-based method is suitable for recognizing dangerous vehicle steering maneuvers.

A new methodology for estimating the grapevine-berry number per cluster using image analysis

A new image analysis algorithm based on mathematical morphology and pixel classification for grapevine berry counting is presented in this paper. First, a set of berry candidates represented by connected components was extracted. Then, six descriptors were calculated using key features of these components, and were employed for false positive (FP) discrimination using a supervised approach. More specifically, the set of descriptors modelled the grapes' distinctive shape, light reflection pattern and colour. Two classifiers were tested, a three-layer neural network and an optimised support vector machine. A dataset of 152 images was acquired with a low-cost smart phone camera. Images came from seven grapevine varieties, 18 per variety, at the two phenological stages in the Baggiolini scale between berry set (named stage K; 94 images) and cluster-closure (named stage L; 32 images). 126 of these images were kept for external validation and the remaining 26 were used for training (12 at stage L and 14 at K). From these training images, 5438 true/false positive samples were generated and labelled in terms of the six descriptors. The neural network performed better than the support vector machine, yielding consistent Recall and Precision average values of 0.9572 and 0.8705, respectively. The presented algorithm, implemented as a smartphone application, can constitute a useful diagnosis tool for the in-the-field and non-destructive yield prediction and berry set assessing for the grape and wine industry.

A Low-Cost Smartphone Sensor-Based UV Camera for Volcanic SO2 Emission Measurements

Recently, we reported on the development of low-cost ultraviolet (UV) cameras, based on the modification of sensors designed for the smartphone market. These units are built around modified Raspberry Pi cameras (PiCams; ≈USD 25), and usable system sensitivity was demonstrated in the UVA and UVB spectral regions, of relevance to a number of application areas. Here, we report on the first deployment of PiCam devices in one such field: UV remote sensing of sulphur dioxide emissions from volcanoes; such data provide important insights into magmatic processes and are applied in hazard assessments. In particular, we report on field trials on Mt. Etna, where the utility of these devices in quantifying volcanic sulphur dioxide (SO2) emissions was validated. We furthermore performed side-by-side trials of these units against scientific grade cameras, which are currently used in this application, finding that the two systems gave virtually identical flux time series outputs, and that signal-to-noise characteristics of the PiCam units appeared to be more than adequate for volcanological applications. Given the low cost of these sensors, allowing two-filter SO2 camera systems to be assembled for ≈USD 500, they could be suitable for widespread dissemination in volcanic SO2 monitoring internationally.

Low-Cost, Robust, and Field Portable Smartphone Platform Photometric Sensor for Fluoride Level Detection in Drinking Water.

Groundwater is the major source of drinking water for people living in rural areas of India. Pollutants such as fluoride in groundwater may be present in much higher concentration than the permissible limit. Fluoride does not give any visible coloration to water, and hence, no effort is made to remove or reduce the concentration of this chemical present in drinking water. This may lead to a serious health hazard for those people taking groundwater as their primary source of drinking water. Sophisticated laboratory grade tools such as ion selective electrodes (ISE) and portable spectrophotometers are commercially available for in-field detection of fluoride level in drinking water. However, such tools are generally expensive and require expertise to handle. In this paper, we demonstrate the working of a low cost, robust, and field portable smartphone platform fluoride sensor that can detect and analyze fluoride concentration level in drinking water. For development of the proposed sensor, we utilize the ambient light sensor (ALS) of the smartphone as light intensity detector and its LED flash light as an optical source. An android application "FSense" has been developed which can detect and analyze the fluoride concentration level in water samples. The custom developed application can be used for sharing of in-field sensing data from any remote location to the central water quality monitoring station. We envision that the proposed sensing technique could be useful for initiating a fluoride removal program undertaken by governmental and nongovernmental organizations here in India.

Ultraviolet Imaging with Low Cost Smartphone Sensors: Development and Application of a Raspberry Pi-Based UV Camera.

Here, we report, for what we believe to be the first time, on the modification of a low cost sensor, designed for the smartphone camera market, to develop an ultraviolet (UV) camera system. This was achieved via adaptation of Raspberry Pi cameras, which are based on back-illuminated complementary metal-oxide semiconductor (CMOS) sensors, and we demonstrated the utility of these devices for applications at wavelengths as low as 310 nm, by remotely sensing power station smokestack emissions in this spectral region. Given the very low cost of these units, ≈ USD 25, they are suitable for widespread proliferation in a variety of UV imaging applications, e.g., in atmospheric science, volcanology, forensics and surface smoothness measurements.

Personal hand-held devices and virtual reality passive technologies for digital heritage browsing: Lesson learnt with the KIVI project

A common issue for 3D real-time displaying concerns the amount of computing resources needed to perform smooth photorealistic sequences. Fast frame-rates and user-responsive interactions are hugely costly in terms of datasets workflows and digital effects processing: real-time cast-shadows, advanced lights effects, depth of view blurring and ambient-occlusion rendering are putting in severe strain the most recent rendering solutions. Certainly, the real-time rendering of architectural and digital heritage artifacts do not need advanced FX sets, commonly involved in multi-user role-games, but instead require very detailed 3D models to permit accurate surveying protocols and detailed scientific observations. The recent (re)discovery of light immersive VR solutions brought to the front outdated problematics, revealed more than 20 years ago with the rise of former Virtual Reality experiments: early Nintendo Virtual Boy (1995) and the NASA's Incredible Helmet (mid 90's) explored personal immersive capabilities but without meeting at that time it's potential market. Today, with the rise of low-cost smartphones mounts, we face similar issues : despite poor computing capabilities, reduced wireless bandwidths and low-polygons 3D models, the KIVI project explores technical and ergonomic opportunities that could today – with the use of personal hand-held technologies - ensure a rewarding experience in the virtual discovery of architectural and heritage artifacts.

Smartphone hearing screening in mHealth assisted community-based primary care

Introduction Access to ear and hearing health is a challenge in developing countries, where the burden of disabling hearing loss is greatest. This study investigated community-based identification of hearing loss using smartphone hearing screening (hearScreen™) operated by community health workers (CHWs) in terms of clinical efficacy and the reported experiences of CHWs. Method The study comprised two phases. During phase one, 24 CHWs performed community-based hearing screening as part of their regular home visits over 12 weeks in an underserved community, using automated test protocols employed by the hearScreen™ smartphone application, operating on low-cost smartphones with calibrated headphones. During phase two, CHWs completed a questionnaire regarding their perceptions and experiences of the community-based screening programme. Results Data analysis was conducted on the results of 108 children (2–15 years) and 598 adults (16–85 years). Referral rates for children and adults were 12% and 6.5% respectively. Noise exceeding permissible levels had a significant effect on screen results at 25 dB at 1 kHz (p<0.05). Age significantly affected adult referral rates (p < 0.05), demonstrating a lower rate (4.3%) in younger as opposed to older adults (13.2%). CHWs were positive regarding the hearScreen™ solution in terms of usability, need for services, value to community members and time efficiency. Conclusion Smartphone-based hearing screening allows CHWs to bring hearing health care to underserved communities at a primary care level. Active noise monitoring and data management features allow for quality control and remote monitoring for surveillance and follow-up.

Indoor Pedestrian Localization With a Smartphone: A Comparison of Inertial and Vision-Based Methods

Indoor pedestrian navigation systems are increasingly needed in various types of applications. However, such systems are still face many challenges. In addition to being accurate, a pedestrian positioning system must be mobile, cheap, and lightweight. Many approaches have been explored. In this paper, we take the advantage of sensors integrated in a smartphone and their capabilities to develop and compare two low-cost, hands-free, and handheld indoor navigation systems. The first one relies on embedded vision (smartphone camera), while the second option is based on low-cost smartphone inertial sensors (magnetometer, accelerometer, and gyroscope) to provide a relative position of the pedestrian. The two associated algorithms are computationally lightweight, since their implementations take into account the restricted resources of the smartphone. In the experiment conducted, we evaluate and compare the accuracy and repeatability of the two positioning methods for different indoor paths. The results obtained demonstrate that the vision-based localization system outperforms the inertial sensor-based positioning system.

QUALITY ASSESSMENT AND COMPARISON OF SMARTPHONE AND LEICA C10 LASER SCANNER BASED POINT CLOUDS

3D urban models are valuable for urban map generation, environment monitoring, safety planning and educational purposes. For 3D measurement of urban structures, generally airborne laser scanning sensors or multi-view satellite images are used as a data source. However, close-range sensors (such as terrestrial laser scanners) and low cost cameras (which can generate point clouds based on photogrammetry) can provide denser sampling of 3D surface geometry. Unfortunately, terrestrial laser scanning sensors are expensive and trained persons are needed to use them for point cloud acquisition. A potential effective 3D modelling can be generated based on a low cost smartphone sensor. Herein, we show examples of using smartphone camera images to generate 3D models of urban structures. We compare a smartphone based 3D model of an example structure with a terrestrial laser scanning point cloud of the structure. This comparison gives us opportunity to discuss the differences in terms of geometrical correctness, as well as the advantages, disadvantages and limitations in data acquisition and processing. We also discuss how smartphone based point clouds can help to solve further problems with 3D urban model generation in a practical way. We show that terrestrial laser scanning point clouds which do not have color information can be colored using smartphones. The experiments, discussions and scientific findings might be insightful for the future studies in fast, easy and low-cost 3D urban model generation field.

QUALITY ASSESSMENT AND COMPARISON OF SMARTPHONE AND LEICA C10 LASER SCANNER BASED POINT CLOUDS

Abstract. 3D urban models are valuable for urban map generation, environment monitoring, safety planning and educational purposes. For 3D measurement of urban structures, generally airborne laser scanning sensors or multi-view satellite images are used as a data source. However, close-range sensors (such as terrestrial laser scanners) and low cost cameras (which can generate point clouds based on photogrammetry) can provide denser sampling of 3D surface geometry. Unfortunately, terrestrial laser scanning sensors are expensive and trained persons are needed to use them for point cloud acquisition. A potential effective 3D modelling can be generated based on a low cost smartphone sensor. Herein, we show examples of using smartphone camera images to generate 3D models of urban structures. We compare a smartphone based 3D model of an example structure with a terrestrial laser scanning point cloud of the structure. This comparison gives us opportunity to discuss the differences in terms of geometrical correctness, as well as the advantages, disadvantages and limitations in data acquisition and processing. We also discuss how smartphone based point clouds can help to solve further problems with 3D urban model generation in a practical way. We show that terrestrial laser scanning point clouds which do not have color information can be colored using smartphones. The experiments, discussions and scientific findings might be insightful for the future studies in fast, easy and low-cost 3D urban model generation field.

Trans-palpebral illumination: an approach for wide-angle fundus photography without the need for pupil dilation.

It is technically difficult to construct wide-angle fundus imaging devices due to the complexity of conventional transpupillary illumination and imaging mechanisms. We report here a new method, i.e., trans-palpebral illumination, for wide-angle fundus photography without the need for pupil dilation. By constructing a smartphone-based prototype imaging device, we demonstrated a 152° view in a single-shot image. The unique combination of low-cost smartphone design and automatic illumination optimization promises an affordable solution to conduct telemedicine assessment of eye diseases, which will improve access to eye care for patients in rural and underserved areas.

Tropical forest tree positioning accuracy: A comparison of low cost GNSS-enabled devices

Today, faster than any previous communication technology, mobile technology such as smartphones, tablet phone and notebook has made a huge difference to the lives of a great number of people. Although one can collect data through a number of traditional channels, e.g. pen and paper and more advanced survey equipment, low cost smartphone and tablet phone are emerging as a good choice. To investigate the potential and performance of Global Navigation Satellite System (GNSS)-enabled smartphone and tablet phone in data collection, a study has been conducted at Forest Research Institute Malaysia (FR1M) Kepong, Kuala Lumpur. Geotrees mobile collector using a Sony Xperia C3 smartphone and Samsung Galaxy Tab 3 were used to geo-locate the attributes of tree species within the area of interest. Comparison was then made using a handheld GPS and a Total Station. The findings indicate that the horizontal positioning accuracy detected by the instruments used in this study were mostly accurate within 5 to 15m. The root mean square (RMS) errors were higher in the areas surrounded by larger canopy diameter trees. Based on the result, despite limited coverage of sky visibility, a GNSS-enabled smartphone and tablet phone was sufficiently adequate to augment the purpose of tree inventory for a certain area, and might suit to serve for low accuracy application.

Clinical Validation of a Smartphone-Based Adapter for Optic Disc Imaging in Kenya.

Visualization and interpretation of the optic nerve and retina are essential parts of most physical examinations. To design and validate a smartphone-based retinal adapter enabling image capture and remote grading of the retina. This validation study compared the grading of optic nerves from smartphone images with those of a digital retinal camera. Both image sets were independently graded at Moorfields Eye Hospital Reading Centre. Nested within the 6-year follow-up (January 7, 2013, to March 12, 2014) of the Nakuru Eye Disease Cohort in Kenya, 1460 adults (2920 eyes) 55 years and older were recruited consecutively from the study. A subset of 100 optic disc images from both methods were further used to validate a grading app for the optic nerves. Data analysis was performed April 7 to April 12, 2015. Vertical cup-disc ratio for each test was compared in terms of agreement (Bland-Altman and weighted κ) and test-retest variability. A total of 2152 optic nerve images were available from both methods (also 371 from the reference camera but not the smartphone, 170 from the smartphone but not the reference camera, and 227 from neither the reference camera nor the smartphone). Bland-Altman analysis revealed a mean difference of 0.02 (95% CI, -0.21 to 0.17) and a weighted κ coefficient of 0.69 (excellent agreement). The grades of an experienced retinal photographer were compared with those of a lay photographer (no health care experience before the study), and no observable difference in image acquisition quality was found. Nonclinical photographers using the low-cost smartphone adapter were able to acquire optic nerve images at a standard that enabled independent remote grading of the images comparable to those acquired using a desktop retinal camera operated by an ophthalmic assistant. The potential for task shifting and the detection of avoidable causes of blindness in the most at-risk communities makes this an attractive public health intervention.

The “Smartstone”: using smartphones as a telehealth gateway for senior citizens

Abstract: A possible solution to reduce healthcare costs in a world that is aging is the adoption of telehealth technologies. Several solutions appeared, in the past suggesting the use of smart devices (mobile phones or tablets) for supporting telehealth. Unfortunately, elderly people may have difficulties in the use of such devices even if user interfaces are becoming friendly and intuitive. This work introduces the concept of “Smartstone”, that is the use of a (low-cost) smartphone as a simple, effective, and portable gateway/edge server for mobile healthcare towards cloud and Internet of Things (IoT) applications. The Smartstone is designed in order to minimize the user interaction, thanks to its autonomous behavior. The adoption of smart devices as a building block ensures state-of-the-art connectivity and relatively high computational power, complemented by an ensemble of additional onboard sensors. In particular, results about the management of a new photoplethysmographic /bio-impedance monitor and a smart pill dispenser are presented in this work.

Using Low-cost Smartphone Sensor Data for Locating Crash Risk Spots in a Road Network

This paper investigates the use of smartphones in vehicle fleets for identifying high-risk locations in a road network, before a crash may have happened. A novel method is proposed on how to use smartphone GPS and motion sensor data to automatically recognize critical car driving situations and near-misses such as emergency braking, evasion manoeuvres or sudden driving speed changes. In the area of Vienna, Austria, approximately 200hours of driving data were collected with a dedicated smartphone app, from about 100 drivers covering more than 8,000km. Additionally, various near-miss manoeuvres were measured on a closed test track under controlled conditions. In post-processing, this data was analysed in terms of driver-specific thresholds for critical driving situations. Results show that by using this modelling approach, critical situations can be accurately identified and geographically located with smartphones. An interface to traffic management would allow near-miss information to be used along accident data in the improvement of safety and efficiency of a traffic system. A combination of the proposed method with digital maps enables future applications for traffic and fleet managers, such as a “road safety hazard map”.