CAR-FINDING SYSTEM WITH COUCHDB-BASED SENSOR MANAGEMENT PLATFORM

Geographic routing protocols have been widely used in microsensor networks, however, they cannot directly apply to distributed mobile sensor systems as mobile sensors often do not know their neighbors' exact physical locations. In this paper we consider geographic routing in distributed sensor systems without location information. We address the problem by introducing a lightweight and distributed virtual coordinate assignment protocol. We focus on the effectiveness of routing algorithms for distributed data fusion in the system and provide a detailed analysis of several routing algorithms for a sensor system with group mobility. Our simulation results show that controlled data flows significantly increase the probability of relevant data being fused

One of the major problems in developing countries is maintenance of roads. Well maintained roads contribute a major portion to the country's economy. Identification of road distress such as potholes and bumps, helps drivers to avoid accidents, vehicle damages and it also helps authorities to maintain roads. In this paper, we discuss the previous pothole detection methods that has been developed and proposes a cost-effective solution to identify the potholes and bumps on roads. In our system, mobile phone sensors are used to identify the potholes and bumps. The proposed system captures the geographical location of the potholes and bumps using GPS sensor in the Mobile phone. These sensed-data are send to the cloud storage for further processing. This serves as a valuable source of information for the government authorities and vehicle drivers. An android and web application can be used to display the road condition in the map.

Mobile sensing has been gaining ground due to the increasing capabilities of mobile and personal devices that are carried around by citizens, giving access to a large variety of data and services based on the way humans interact. Mobile sensing brings several advantages in terms of the richness of available data, particularly for human activity recognition. Nevertheless, the infrastructure required to support large-scale mobile sensing requires an interoperable design, which is still hard to achieve today. This review paper contributes to raising awareness of challenges faced today by mobile sensing platforms that perform learning and behavior inference with respect to human routines: how current solutions perform activity recognition, which classification models they consider, and which types of behavior inferences can be seamlessly provided. The paper provides a set of guidelines that contribute to a better functional design of mobile sensing infrastructures, keeping scalability as well as interoperability in mind.

A vehicle-mounted mobile mid-infrared dual-gas sensor system for simultaneous detection of methane (CH₄) and ethane (C₂H₆) was developed using two interband cascade lasers (ICLs) for targeting the absorption line of CH₄ at 3038.5 cm^-1 and the line of C₂H₆ at 2996.88 cm^-1, respectively. Two multi-pass gas cells (MPGCs) with an absorption path length of 26.4 m were utilized. The detection limit (1σ) of CH₄ using wavelength modulation spectroscopy (WMS) is ~ 4.1 parts-per-billion by volume (ppbv) with a 0.5 s averaging time, and the detection limit (1σ) of C₂H₆ is ~ 2.9 ppbv with a 0.5 s averaging time. Vehicle-mounted mobile measurement ability of the dual-gas sensor was enabled by a remote monitoring system based on an embedded Linux processor and a cloud server. Atmospheric CH₄ and C₂H₆ monitoring was performed for 48 hours on the Jilin University campus to evaluate the performance of the sensor system. Vehicle-mounted mobile campaigns were carried out both on the Jilin University campus and in the Changchun Area for dual-gas concentration mapping. The sensor system shows the merits of remote monitoring and mobile gas sensing ability in field applications.

The main purpose of this thesis is to introduce an intelligent home control system which is based on MCU(EM78F668N), the PC(personal computer), wireless transceiver module FHL0611 as the core, to control the external temperature sensors, humidity sensors, light sensor and solar heating system. Thus the system achieves the automatic control of indoor home environment and use a wireless terminal on the indoor home of the remote control. This article also gives the device hardware and software design and implementation.

Mobile sensor networks are the most promising solution to cover an Area of Interest (AoI) in safety critical scenarios. Mobile devices can coordinate with each other according to a distributed deployment algorithm, without resorting to human supervision for device positioning and network configuration. In this paper, we focus on the vulnerabilities of the deployment algorithms based on Voronoi diagrams to coordinate mobile sensors and guide their movements. We give a geometric characterization of possible attack configurations, proving that a simple attack consisting of a barrier of few compromised sensors can severely reduce network coverage. On the basis of the above characterization, we propose two new secure deployment algorithms, named SecureVor and Secure Swap Deployment (SSD). These algorithms allow a sensor to detect compromised nodes by analyzing their movements, under different and complementary operative settings. We show that the proposed algorithms are effective in defeating a barrier attack, and both have guaranteed termination. We perform extensive simulations to study the performance of the two algorithms and compare them with the original approach. Results show that SecureVor and SSD have better robustness and flexibility and excellent coverage capabilities and deployment time, even in the presence of an attack.

Collection of epidemiological data and care of patients are hampered by lack of access to laboratory diagnostic equipment and patients' health records in resource-limited settings. We engineered a low-cost mobile device that combines cell-phone and satellite communication technologies with fluid miniaturization techniques for performing all essential ELISA functions. We assessed the device's ability to perform HIV serodiagnostic testing in Rwanda and synchronize results in real time with electronic health records. We tested serum, plasma, and whole blood samples collected in Rwanda and on a commercially available sample panel made of mixed antibody titers. HIV testing on 167 Rwandan patients evaluated for HIV, viral hepatitis, and sexually transmitted infections yielded diagnostic sensitivity and specificity of 100% and 99%, respectively. Testing on 40 Rwandan whole-blood samples-using 1 μL of sample per patient-resulted in diagnostic sensitivity and specificity of 100% and 100%. The mobile device also successfully transmitted all whole-blood test results from a Rwandan clinic to a medical records database stored on the cloud. For all samples in the commercial panel, the device produced results in agreement with a leading ELISA test, including detection of weakly positive samples that were missed by existing rapid tests. The device operated autonomously with minimal user input, produced each result 10 times faster than benchtop ELISA, and consumed as little power as a mobile phone. A low-cost mobile device can perform a blood-based HIV serodiagnostic test with laboratory-level accuracy and real-time synchronization of patient health record data.

The strain of manual, automated, and semi-automated tasks in high-throughput chemical screening procedures offer new challenges for occupational and preventive medicine. Therefore, field inquiries need to measure several physiological parameters to determine amounts of strain. These include blood pressure, heart rate, and breathing parameters. These parameters can be registered by specialized mobile devices and sensor systems, but before they can be evaluated, it is essential to understand the activity patterns that represent the workloads. Activity status is gathered by those being tested with the help of a Nokia 3660 cell phone. A self-developed software module runs on the mobile phone and allows users to enter an activity setting and any subjective conditions via a short questionnaire. All data are stored together with a time stamp. After finishing an experiment (i.e., completing a working day), the collected data are transmitted to a central data server. Activity data and physiological data are stored in a central database in a merged data set. Access is provided via an Intranet or Internet connection. A graphical visualization tool, which can be shared from any location via Internet, helps to analyze the experimental data. Occupational medicine field studies in the working environment of chemical laboratories benefit from the data acquisition system and especially from the semiautomated self-monitoring.

A wide range of medical devices have significant electronic components. Compared to open-source medical software, open (and open-source) electronic hardware has been less published in peer-reviewed literature. In this review, we explore the developments, significance, and advantages of using open platform electronic hardware for medical devices. Open hardware electronics platforms offer not just shorter development times, reduced costs, and customization; they also offer a key potential advantage which current commercial medical devices lack—seamless data sharing for machine learning and artificial intelligence. We explore how various electronic platforms such as microcontrollers, single board computers, field programmable gate arrays, development boards, and integrated circuits have been used by researchers to design medical devices. Researchers interested in designing low cost, customizable, and innovative medical devices can find references to various easily available electronic components as well as design methodologies to integrate those components for a successful design.

In this paper a system level analysis and implementation of two-layer mobile wireless sensor network architecture is proposed for tracking and environmental supervision applications. It uses a mobile Master Sensor Node (MSN) that collects information inside a Sensor Area Network (SAN) where many semi-passive Slave Sensor Nodes (SSN) are deployed. The collected information is sent through a Wireless Wide Area Network (WWAN) infrastructure to a central server via TCP/UDP. The communication interface between the user and the MSN is established through out mobile communication services or internet mail services. The communication between the MSN and the SSN is through asymmetric-link Radio Frequency Identification (RFID) based architecture. An MSN prototype has been implemented and tested under real conditions for environmental supervision during the perishable goods transportation.

Welcome to the First ACM workshop on mobile systems, applications, and services for healthcare, co-held with ACM SenSys 2011 in Seattle, Washington, USA. This is the first workshop at SenSys which explores the intersection of mobile systems, sensor systems, and medical informatics. This workshop explores, encourages, and accelerates advances in wearable sensing, mobile phone sensing, algorithms, applications, and services that aim to deliver healthcare in the unconstrained mobile environment of individuals. The first year's program includes keynotes from the medical and technological community, Charlene Quinn and Aydogan Ozcan, along with 6 research papers and 7 demos. We will also have a panel on setting the research agenda for mHealth in 2020, participants include Santosh Kumar (moderator), George Demiris, David McDonald, Babak Parviz, and Mani Srivastava. We are pleased by the program of the workshop with the medical and technological communities participating in exploring the frontiers of mobile technology in healthcare. The workshop will also be presenting the best paper and best demo awards. We thank the Technical Program committee chaired by Santosh Kumar and Kenneth Watkin for putting together a wonderful program. We received 17 high-quality submissions to mHealthSys 2011 workshop. Each paper was reviewed by at least three members of the technical program committee; most papers received 4-5 reviews. A TPC meeting was held to discuss the papers and their reviews to make a final decision. Only 6 out of the 17 submitted papers (i.e., 35%) were accepted to the final program.

2016 IEEE 13th International Conference on Mobile Ad Hoc and Sensor Systems (MASS)

In this paper, a silicon resonant cantilever sensor is used for monitoring airborne nanoparticles (NPs) by detecting the resonant frequency shift that is directly induced by an additional NPs mass deposited on it. A piezoelectric stack actuator and a self-sensing technique using a piezoresistive strain gauge are involved in the sensor system in order to actuate and detect the oscillation of cantilever sensor, respectively. The dielectrophoresis (DEP) method is employed for trapping the airborne NPs in a stable carbon aerosol assessment. A thermal-induced frequency shift is also investigated with the purpose of observing the limitation imposed by thermal effects on the minimum detectable NPs mass. The proposed sensor reveals a mass sensitivity of 8.33 Hz/ng, a fundamental resonant frequency of 43.92 kHz, a quality factor of 1230, and a temperature coefficient of the resonant frequency (TC <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">f</sub> ) of -28.6 ppm/°C. The results demonstrate a possibility of using this resonant cantilever in mobile airborne sensor applications.

2018 IEEE 15th International Conference on Mobile Ad Hoc and Sensor Systems (MASS)

2017 IEEE 14th International Conference on Mobile Ad Hoc and Sensor Systems (MASS)