Electric double-layer capacitors, also known as supercaps, have several advantages over traditional energy buffers: They do not require complex charging circuits, offer virtually unlimited charge-discharge cycles, and generally enable easy state-of-charge assessment. A closer look yet reveals that leakage and internal reorganization effects hamper state-of-charge assessment by means of terminal voltage, particularly after a charging cycle. Sophisticated models capture this effect at the cost of an increased calculation and parameter-estimation complexity. As this is hardly feasible on low-power, low-resource sensor nodes, we evaluate the performance of simple models on a real energy-harvesting sensor node platform. We show that model errors are as low as 1-2% on average and never exceed 5% in our experiments, supporting that there is no need to employ more complex models on common sensor node platforms, equipped with unreliable ADC readings and uncertain consumption due to hardware variation in the same order of magnitude.
Opportunistic data collection in wireless sensor networks uses passing smartphones to collect data from sensor nodes, thus avoiding the cost of multiple static sink nodes. Based on the observed mobility patterns of smartphone users, sensor data should be preforwarded to the nodes that are visited more frequently with the aim of improving network throughput. In this article, we construct a formal network model and an associated theoretical optimization problem to maximize the throughput subject to energy constraints of sensor nodes. Since a centralized controller is not available in opportunistic data collection, data pre-forwarding (DPF) must operate as a distributed mechanism in which each node decides when and where to forward data based on local information. Hence, we develop a simple distributed DPF mechanism with two heuristic algorithms, implement this proposal in Contiki-OS, and evaluate it thoroughly. We demonstrate empirically, in simulations, that our approach is close to the optimal solution obtained by a centralized algorithm. We also demonstrate that this approach performs well in scenarios based on real mobility traces of smartphone users. Finally, we evaluate our proposal on a small laboratory testbed, demonstrating that the distributed DPF mechanism with heuristic algorithms performs as predicted by simulations, and thus that it is a viable technique for opportunistic data collection through smartphones.
Among various application scenarios of Internet of Things (IoT) technology, Building Energy Management System (BEMS) is one of the most promising applications considering the sustainable development trend in the world. With progress of related technologies, the BEMS can gather more and more applications into itself. But the development also involves an issue which is huge data transferring and processing. This paper provides a multiple gateway system for wireless sensor network (WSN) management in BEMS, and also provides an efficient data transmission method for sensor data collection. The multiple gateway system includes at least a main gateway, several terminal gateway and more sensor nodes. These sensor nodes find a nearest terminal gateway and access to its LAN, and send data to it. The terminal gateway with a control module on it, can collect information of every neighbor gateway including gateway buffer size and distance to itself, and then optimize routing according to gateway information, and finally sends data to main gateway timely. The main gateway can process data like data fusion, and users can access these data via LAN or Internet. Using these multiple gateway system, the network power consumption and data delay can be both decreased, thereby promoting the system working efficiency.
In this paper we present a Platform-as-a-Service (PaaS) approach for rapid development of wireless sensor network (WSN) applications based on the dinam-mite concept, i.e. an embedded web-based development environment and run-time platform for WSN systems integrated in a single information appliance. The PaaS is hosted by a cloud of dinam-mite nodes which facilitates the on-demand development, deployment and integration of WSN applications. We introduce the dinam Cloud architecture and focus, in this paper, on the PaaS layer established by the dinam-mite nodes. In addition to the description of this so-called dinam PaaS, a performance analysis of the dinam-mite node towards its applicability to forming a dinam PaaS layer is demonstrated. We then present the MASON mobile vehicular network as an example of such a WSN which delivers spatially and temporally fine-grained environmental measurements within the city of Beijing, and illustrate how to utilize the dinam PaaS for integrating the data from the MASON network into its back-end business system. Finally, we discuss the five essential properties of the Cloud Computing stack, according to the NIST definition, with respect to the dinam PaaS and illustrate the benefits of the dinam PaaS for system integration as well as WSN application development.
This paper presents a novel capacitive tactile sensor with high sensitivity for humanoid robots. The main structure of the sensor is a cubic `box' (3 × 3 × 2.5 mm 3 ) made of Polydimethylsiloxane (PDMS). Two dielectric liquids, i.e. a polyalcohol droplet (with a higher dielectric constant) surrounded by oil (with a lower dielectric constant), were sealed in the box under iso-density condition. Electrodes were fabricated on the upper and lower inner surfaces of the box to form a capacitor. The two liquids, sandwiched by the electrodes, increased the capacitance of the capacitor. The sensitivity of the sensor increased due to the novel configuration. The proposed sensor was fabricated by microfabrication technology. This sensor's sensitivity is 61.77%/N, which is 3.3 times greater than that of typical sensors containing no liquid.
This paper proposes a method to detect small-waving hand from image sequences. The method is based on frequency analysis of intensity value change for each pixel of low-resolution images converted from input images. Handwaving makes periodical change of intensity value of image pixels located in the moving region. The periodical change is detected by thresholding of a value accumulating frequency features obtained through FFT calculation. The proposed method can stably detect small-waving hand with 3-5 Hz in a range of 2-6 m. We demonstrate an application of spatial memory through measuring 3D position of small-waving hand detected by a distributed camera system.
The Internet of Things allows physical objects, sensors, and actuators to be connected to each other as well as cloud services. Over the past few years, advances in wireless protocols, software systems, and standardization for IPv6 points to a future where every physical object that can benefit from an Internet connection will be connected to the Internet. This paper presents the IPv6 networking support in the Contiki operating system, the system that first introduced the concept of IP networking for low-power wireless systems. We discuss the design and implementation of IPv6 in Contiki as well as the methods used to develop and evaluate low-power mechanisms.
Sensor nodes in wireless sensor networks (WSNs) are often powered by energy harvesting devices used to extend the lifetime of the nodes and energy storage elements are fundamental to collect the exceeding power incoming from the ambient. The stored energy is then consumed to supply the sensor node when the ambient energy is scarce or insufficient to satisfy the current requests from the load. To date, the choice of the storage element is made between rechargeable batteries and electric double-layer capacitors (EDLC or supercapacitors), and many works in literature exploit hybrid storage architectures. In this paper we characterize an innovative technology available on the market, namely the lithium-ion capacitor (LIC). We show that this cutting edge technology combines the high cell voltage, the energy density and the low self-discharge of a lithium battery with the power density, the high capacity and long cycle life of a supercapacitor.
We demonstrate deploying continuations dynamically into heterogeneous wireless sensor networks. Continuations include the computation code, collected sensor-based data and a partial view of the sensor network nodes, where the continuation travels. Here, continuations are considered resources in a sensor network and can be exposed to the world by means of the Computational REST. Services in the network can be dynamically composed from these continuations. This method has many uses in sensing and integrating sensor network's resources with the Web. We also provide simple mapping of the continuation structure to Constrained Application Protocol message structure. We demonstrate this method in IP-based resource constrained wireless sensor network.
In a sheet design of the two-dimensional communication (2DC) system, it is desirable to add shielding metal walls to the edges of the sheet in order to suppress electromagnetic (EM) radiation. Then, the sheet medium has the cutoff frequency similar to a rectangular waveguide, which can be determined from the width of the sheet. If the carrier frequency is less than the cutoff frequency, the power cannot be transmitted through the sheet. This paper proposes a new narrow 2DC sheet with the cutoff frequency lower than a conventional 2DC sheet with metal walls. Actually, the lower cutoff frequency can be obtained by forming a special metal pattern near the shielded walls. This can make the sheet width wider equivalently (electrical length longer). Then EM wave can propagate through a narrower sheet. Measurements using fabricated prototypes clearly show the advantage of the proposed structure.
A variety of studies in the past decades have shown that fine particulate matter can be a serious health hazard, contributing to respiratory and cardiovascular disease. Due to this, more and more regulations defining certain permissible concentration limits have been set by governments around the world. However, current standard measurement equipment is large, expensive and sparsely deployed. Additionally, both the exposure to hazardous conditions and the susceptibility to negative health effects vary from person to person. As a result, we see the need for fine-grained, mobile and distributed measurements, e.g. to identify hot spots or monitor people at risk. Our research investigates the feasibility of particulate matter measurements using cheap, commodity dust sensors which are small enough to be incorporated into mobile devices. This paper first discusses application scenarios which would benefit from inexpensive methods to assess the particulate matter load. Subsequently, commercial-off-the-shelf (COTS) sensors are compared and their general suitability for the application scenarios is examined. Finally, an experimental setup for the evaluation of one of the sensors is presented along with preliminary results.
One important application scenario of ad-hoc wireless sensor networks is fire alarming which is considered in this paper. Although the speed of the network to report and monitor the situation has key role to decrease the damages, resource restricted and limited accessible bandwidth limit the packet delivery speed severely. In this paper, we applied the special packet generation pattern in such scenarios to optimize channel access schedule. We modified the back-off algorithm as a part of IEEE 802.11 Distributed Coordination Function (DCF). In the special case of Binary Exponential Back-off Algorithm (BEBA), we showed numerically how the performance of the network degrades due to the dramatically high increase in the packet generation rate. Our proposed modifications spanning static and dynamic situations outperforms the standard algorithm.
Because of the intrinsic advantages of wireless inertial motion tracking, standalone devices that integrate inertial motion units with wireless networking capabilities have gained much interest in recent years. Several platforms, both commercially available and academic, have been proposed to balance the challenges of a small form-factor, power consumption, accuracy and processing speed. Applications include ambulatory monitoring to support healthcare, sport activity analysis, recognizing human group behaviour, navigation support for humans, robots and unmanned vehicles, but also in structural monitoring of large buildings. This paper provides an analysis of the current state-of-the-art platforms in wireless inertial motion tracking and presents a novel open-source and open-hardware hybrid tracking platform that is extensible, low-power, flexible enough to be used for both short- and long-term monitoring and based on a firmware that allows it to be easily adapted after being deployed.
This paper develops algorithms for improved source selection in social sensing applications that exploit social networks (such as Twitter, Flickr, or other mass dissemination networks) for reporting. The collection point in these applications would simply be authorized to view relevant information from participating clients (either by explicit client-side action or by default such as on Twitter). Social networks, therefore, create unprecedented opportunities for the development of sensing applications, where humans act as sensors or sensor operators, simply by posting their observations or measurements on the shared medium. Resulting social sensing applications, for example, can report traffic speed based on GPS data shared by drivers, or determine damage in the aftermath of a natural disaster based on eye-witness reports. A key problem, when dealing with human sources on social media, is the difficulty in ensuring independence of measurements, making it harder to distinguish fact from rumor. This is because observations posted by one source are available to its neighbors in the social network, who may, in-turn, propagate those observations without verifying their correctness, thus creating correlations and bias. A corner-stone of successful social sensing is therefore to ensure an unbiased sampling of sources that minimizes dependence between them. This paper explores the merits of such diversification. It shows that a diversified sampling is advantageous not only in terms of reducing the number of samples but also in improving our ability to correctly estimate the accuracy of data in social sensing.
It is generally considered a trivial task to synchronize time in a distributed sensor network having a GPS module on board for each sensor node. This is not quite true depending on the application at hand. Commissioned to implement YuShanNet, a delay-tolerant sensor network (DTSN) enabling encounter information collection for hiker search and rescue, we find that the naive use of standard GPSs time acquisition functionalities gives a synchronization error at the scale of 10-100s milliseconds, which is not sufficient given two application-specific considerations: (1) data goodput and (2) energy efficiency. The two requirements are crucial in that the matter is life or death and the hiking trips usually take days. Towards efficient use of the intermittent connectivity in YuShanNet, we design, implement, and evaluate a time synchronization mechanism that improves the synchronization accuracy by approximately two orders of magnitude. This enables TDMA-fashioned MAC for high-goodput data transmission while the GPS is duty-cycled for energy efficiency.
This paper examines the possibility of 30 W (more exactly 34 W) power transmission through 2D waveguide (2DW) sheet satisfying electromagnetic compatibility (EMC) requirements. The system enables wireless charging to ubiquitous robots for generating a flexible communication network. As the riskiest case in general environments, we suppose a resonant metal plate is put on a 2DW sheet. The radiated power density from any metal plates should be less than the guideline provided by International Commission on Non-Ionizing Radiation Protection (ICNIRP). Satisfying this condition, we achieve safe 30-W transmissions by thickening the surface insulator layer of 2DW to 5 cm and enlarging the coupler size to 30 by 43 cm.
Recent study has shown that the pulse wave signal of human includes much information of human's mental condition. To get such information, measuring finger pulse wave is a non-invasive and convenient method. Then we analyze the measured pulse wave in frequency domain to investigate low- and high-frequency components whose the ratio can be used to estimate mental condition. We design and implement an API to retrieve user's mental state easily and adaptively control a mobile phone's software based on mental condition. To validate the benefit of API, we develop a mail filtering app on an Android phone and perform an experiment.
MAC protocols for multi-hop WSNs have to address the challenge of coordinating duty-cycling transmitters with duty-cycling receivers. All the suggested protocols can be classified into three basic paradigms: the synchronization, the preamble and the beaconing paradigm. In this paper, we discuss the suitability of the three paradigms in the context of Energy Harvesting - Wireless Sensor Networks (EH-WSNs) in which nodes are powered by energy that they harvest from their surrounding environment. The two suitable paradigms are modeled and compared to each other. The analysis indicates the specific conditions under which a scheme is more suitable than the other.
Two-dimensional waveguide power transmission (2DWPT) has been recently improved in efficiency and in electromagnetic compatibility (EMC). In this paper, we present the first EMC-compliant 2DWPT-powered wireless sensor system. The efficiency, from the RF input into the sheet to the dc output of a rectifying coupler, is 40.4% at a maximum, where the sheet has nearly 100 times larger area than the coupler. The first 2DWPT-powered sensor platform device is developed by integrating the high-efficiency rectifying coupler and a Bluetooth data acquisition/transmission module. We present a trial system in which a dc output voltage of an arbitrary sensor connected to the analog input port is monitored on the remote computer every 100 milliseconds in real-time. The proposed device can support power-consuming continuous data-streaming without battery life limitation.
This paper presents a novel approach to adapting software components in sensor networks. It is inspired by the notions of (de)differentiation in cellular slime molds. When a software component delegates a function to another component coordinating with it, if the former has the function, this function becomes less-developed and the latter's function becomes well-developed. The approach enables sensor networks to adapt to changes in the environments, networks, and applications in a self-organizing manner, and is constructed as a middleware system to execute general-pur pose applications on distributed systems, including sensor networks. We present several evaluations of the approach in sensor network settings.
