Combining multiple proximal sensors within a wireless sensor network (WSN) enhances our capacity to monitor vegetation, compared to using a single sensor or non-networked setup. Data from sensors with different spatial and temporal characteristics can provide complementary information. For example, point-based sensors such as multispectral sensors which monitor at high temporal frequency but, at a single point, can be complemented by array-based sensors such as digital cameras which have greater spatial resolution but may only gather data at infrequent intervals. In this article we describe the successful deployment of a prototype system for using multiple proximal sensors (multispectral sensors and digital cameras) for monitoring pastures. We show that there are many technical issues involved in such a deployment, and we share insights relevant for other researchers who may consider using WSNs for an operational deployment for pasture monitoring under often difficult environmental conditions. Although the sensors and infrastructure are important, we found that other issues arise and that an end-to-end workflow is an essential part of effectively capturing, processing and managing the data from a WSN. Our deployment highlights the importance of testing and ongoing monitoring of the entire workflow to ensure the quality of data captured. We demonstrate that the combination of different sensors enhances our ability to identify sensor problems necessary to collect accurate data for pasture monitoring. Full article

Timely dissemination of required state information poses a significant challenge in the design of distributed sensor/actuator network-based control systems. In this paper, distance sensitivity properties inherent in many sensor-actuator network-based control systems are exploited to establish conditions under which information within a bounded locality of each controller closely approximates optimal control based on knowledge of system-wide state information. By doing so, it is shown that optimal control in extremely large-scale distributed control systems can be achieved in O(1) time using information only within a fixed neighborhood around each controller, the size of which depends on the decay characteristics of the actuator influence matrix. Full article

When camera-enabled sensors are deployed for visual monitoring, a new set of innovative applications is allowed, enriching the use of wireless sensor network technologies. In these networks, energy-efficiency is a highly desired optimization issue, mainly because transmission of images and video streams over resource-constrained sensor networks is more stringent than transmission of conventional scalar data. Due to the nature of visual monitoring, that follows a directional sensing model, camera-enabled sensors may have different relevancies for the application, according to the desired monitoring tasks and the current sensors’ poses and fields of view. Exploiting this concept, each data packet may be associated with a priority level related to the packet’s origins, which may be in turn mapped to an energy threshold level. In such way, we propose an energy-efficient relaying mechanism where data packets are only forwarded to the next hop if the associated energy threshold level is below the current energy level of the relaying node. Thus, packets from low-relevant source nodes will be silently dropped when the current energy level of intermediate nodes run below the pre-defined thresholds. Doing so, energy is saved potentially prolonging the network lifetime. Besides the sensing relevancies of source nodes, the relevance of DWT subbands for reconstruction of original images is also considered. This allows the creation of a second level of packet prioritization, assuring a minimal level of image quality even for the least relevant source nodes. We performed simulations for the proposed relaying mechanism, assessing the expected performance over a traditional relaying paradigm. Full article

Convergecast is the transmission paradigm used by data gathering applications in wireless sensor networks (WSNs). For efficiency reasons, a collision-free slotted medium access is typically used: time slots are assigned to non-conflicting transmitters. Furthermore, in any slot, only the transmitters and the corresponding receivers are awake, the other nodes sleeping in order to save energy. Since a multichannel network increases the throughput available to the application and reduces interference, multichannel slot assignment is an emerging research domain in WSNs. First, we focus on a multichannel time slot assignment that minimizes the data gathering delays. We compute the optimal time needed for a raw data convergecast in various multichannel topologies. Then, we focus on how to adapt such an assignment to dynamic demands of transmissions (e.g., alarms, temporary additional application needs and retransmissions). We formalize the problem using linear programming, and we propose an incremental technique that operates on an optimized primary schedule to provide bonus slots to meet new transmission needs. We propose AMSA, an Adaptive Multichannel Slot Assignment algorithm, which takes advantage of bandwidth spatial reuse, and we evaluate its performances in terms of the number of slots required, slot reuse, throughput and the number of radio state switches. Full article

In this paper, we describe how information obtained from multiple views usinga network of cameras can be effectively combined to yield a reliable and fast humanactivity recognition system. First, we present a score-based fusion technique for combininginformation from multiple cameras that can handle the arbitrary orientation of the subjectwith respect to the cameras and that does not rely on a symmetric deployment of thecameras. Second, we describe how longer, variable duration, inter-leaved action sequencescan be recognized in real-time based on multi-camera data that is continuously streaming in.Our framework does not depend on any particular feature extraction technique, and as aresult, the proposed system can easily be integrated on top of existing implementationsfor view-specific classifiers and feature descriptors. For implementation and testing of theproposed system, we have used computationally simple locality-specific motion informationextracted from the spatio-temporal shape of a human silhouette as our feature descriptor.This lends itself to an efficient distributed implementation, while maintaining a high framecapture rate. We demonstrate the robustness of our algorithms by implementing them ona portable multi-camera, video sensor network testbed and evaluating system performanceunder different camera network configurations. Full article

Wireless sensor networks (WSNs) have been a widely researched field since the beginning of the 21st century. The field is already maturing, and TinyOS has established itself as the de facto standard WSN Operating System (OS). However, the WSN researcher community is still active in building more flexible, efficient and user-friendly WSN operating systems. Often, WSN OS design is based either on practical requirements of a particular research project or research group's needs or on theoretical assumptions spread in the WSN community. The goal of this paper is to propose WSN OS design rules that are based on a thorough survey of 40 WSN deployments. The survey unveils trends of WSN applications and provides empirical substantiation to support widely usable and flexible WSN operating system design. Full article

The smart-house technology aims to increase home automation and security with reduced energy consumption. A smart house consists of various intelligent sensors and actuators operating on different platforms with conflicting objectives. This paper proposes a multi-agent system (MAS) design framework to achieve smart house automation. The novelties of this work include the developments of (1) belief, desire and intention (BDI) agent behavior models; (2) a regulation policy-based multi-agent collaboration mechanism; and (3) a set of metrics for MAS performance evaluation. Simulations of case studies are performed using the Java Agent Development Environment (JADE) to demonstrate the advantages of the proposed method. Full article

Bluetooth Low Energy (BLE) is a recently developed energy-efficient short-range wireless communication protocol. In this paper, we discuss and compare the maximum peer-to-peer throughput, the minimum frame turnaround time, and the energy consumption for three protocols, namely BLE, IEEE 802.15.4 and SimpliciTI. The specifics and the main contributions are the results both of the theoretical analysis and of the empirical measurements, which were executed using the commercially available hardware transceivers and software stacks. The presented results reveal the protocols’ capabilities and enable one to estimate the feasibility of using these technologies for particular applications. Based on the presented results, we draw conclusions regarding the feasibility and the most suitable application scenarios of the BLE technology. Full article

This paper presents the theoretical analysis, simulation results and suggests design in digital technology of a physical layer for wireless sensor networks. The proposed design is able to mitigate fading inside communication channel. To mitigate fading the chip interleaving technique is proposed. For the proposed theoretical model of physical layer, a rigorous mathematical analysis is conducted, where all signals are presented and processed in discrete time domain form which is suitable for further direct processing necessary for devices design in digital technology. Three different channels are used to investigate characteristics of the physical layer: additive white Gaussian noise channel (AWGN), AWG noise and flat fading channel and AWG noise and flat fading channel with interleaver and deinterleaver blocks in the receiver and transmitter respectively. Firstly, the mathematical model of communication system representing physical layer is developed based on the discrete time domain signal representation and processing. In the existing theory, these signals and their processing are represented in continuous time form, which is not suitable for direct implementation in digital technology. Secondly, the expressions for the probability of chip, symbol and bit error are derived. Thirdly, the communication system simulators are developed in MATLAB. The simulation results confirmed theoretical findings. Full article

Over the past decade, wireless sensor network research primarily relied on highly-integrated commercial off-the-shelf radio chips. The rigid silicon implementation of the radio stack restricted access to the lower layers; thus, research focused mainly on the medium access control (MAC) layer and above. SRAM field-programmable gate array (FPGA)-based software-defined radios (SDR), on the other hand, provide a flexible architecture to experiment with any and all layers of the radio stack, but usually require desktop computers and draw high currents that prohibit mobile or longer-term outdoor deployments. To address these issues, we have developed a modular flash FPGA-based wireless research platform, called Marmote SDR, that has computational resources comparable to those of SRAM FPGA-based radio platforms, but at a reduced power consumption, with duty cycling support. We discuss the design decisions underlying Marmote SDR and evaluate its power consumption. Furthermore, we present and evaluate an asynchronous and multiple access communication protocol specifically designed for data-gathering wireless sensor networks. Full article