Centroid based 3D localization technique using RSSI with a mobile robot

Knowledge of sensor node 3D location in a sensor network is more important, because many practical applications needs to know the location of sensor data source. This paper presents a new technique for finding indoor 3D location of a sensor node by using Received Signal Strength Indication (RSSI). Proposed localization algorithm is derived from centroid algorithm with composition of empirical path loss model. It gives less error in estimating 3D location of sensor node in a sensor network when compared to its actual location. Algorithm has been implemented and analysed by using IITH motes and a Mobile Robot

SensLAB Very Large Scale Open Wireless Sensor Network Testbed

International audienceThis paper presents a precise description of SensLAB: Very Large Scale Open Wireless Sensor Network Testbed that has been developed and deployed in order to allow the evaluation of scalable wireless sensor network protocols and applications. SensLAB's main and most important goal is to o er an accurate open access multi-users scienti c tool to support the design, development, tuning, and experimentation of real large-scale sensor network applications. The SensLAB testbed is composed of 1024 nodes and it is distributed among 4 sites. Two sites o er access to mobile nodes. Every sensor node is also able to be con gured as a sink node and can exchange data with any other sink node of the whole SensLAB testbed (locally or remotely) or any computer on the Internet. The hardware designed on purpose and software architectures that allow to reserve, con gure, deploy embedded software, boot wireless sensor nodes and gather experimental data and monitoring information are described in details. We also present short demonstration examples to illustrate the use of the SensLAB testbed

On the Support of Massive Machine-to-Machine Traffic in Heterogeneous Networks and Fifth-Generation Cellular Networks

The widespread availability of many emerging services enabled by the Internet of Things (IoT) paradigm passes through the capability to provide long-range connectivity to a massive number of things, overcoming the well-known issues of ad-hoc, short-range networks. This scenario entails a lot of challenges, ranging from the concerns about the radio access network efficiency to the threats about the security of IoT networks. In this thesis, we will focus on wireless communication standards for long-range IoT as well as on fundamental research outcomes about IoT networks. After investigating how Machine-Type Communication (MTC) is supported nowadays, we will provide innovative solutions that i) satisfy the requirements in terms of scalability and latency, ii) employ a combination of licensed and license-free frequency bands, and iii) assure energy-efficiency and security

Machine Learning in Wireless Sensor Networks: Algorithms, Strategies, and Applications

Wireless sensor networks monitor dynamic environments that change rapidly over time. This dynamic behavior is either caused by external factors or initiated by the system designers themselves. To adapt to such conditions, sensor networks often adopt machine learning techniques to eliminate the need for unnecessary redesign. Machine learning also inspires many practical solutions that maximize resource utilization and prolong the lifespan of the network. In this paper, we present an extensive literature review over the period 2002-2013 of machine learning methods that were used to address common issues in wireless sensor networks (WSNs). The advantages and disadvantages of each proposed algorithm are evaluated against the corresponding problem. We also provide a comparative guide to aid WSN designers in developing suitable machine learning solutions for their specific application challenges.Comment: Accepted for publication in IEEE Communications Surveys and Tutorial

Current Advances in Internet of Underground Things

The latest developments in Internet of Underground Things are covered in this chapter. First, the IOUT Architecture is discussed followed by the explanation of the challenges being faced in this paradigm. Moreover, a comprehensive coverage of the different IOUT components is presented that includes communications, sensing, and system integration with the cloud. An in-depth coverage of the applications of the IOUT in various disciplines is also surveyed. These applications include areas such as decision agriculture, pipeline monitoring, border control, and oil wells

Decision Agriculture

In this chapter, the latest developments in the field of decision agriculture are discussed. The practice of management zones in digital agriculture is described for efficient and smart faming. Accordingly, the methodology for delineating management zones is presented. Modeling of decision support systems is explained along with discussion of the issues and challenges in this area. Moreover, the precision agriculture technology is also considered. Moreover, the chapter surveys the state of the decision agriculture technologies in the countries such as Bulgaria, Denmark, France, Israel, Malaysia, Pakistan, United Kingdom, Ukraine, and Sweden. Finally, different field factors such as GPS accuracy and crop growth are also analyzed

System Development for Geolocation in Harsh Environments

Wireless sensor networks (WSN) consist of a set of distributed devices equipped with multiple sensors, which can be employed in different environments of varying characteristics. Nowadays, node localization has become one of their most basic and important requirements. Due to the nature of certain environments, typical positioning systems, such as Global Navigation Satellite System (GNSS), cannot be employed. Therefore, in recent years several alternative positioning mechanisms have risen. ROMOVI is a project which has as its main goal the development of low cost autonomous robots capable of monitoring and perform logistic tasks on the steep slopes of the Douro river vineyards. Integrated in this project, this dissertation proposes the development of a full-custom wireless communication system for geolocation purposes in harsh environments. Using a Symmetric Double Sided Two Way Ranging (SDS-TWR) algorithm, it is possible to achieve ranging measures between nodes, thus providing accurate relative positioning. This work focuses mainly on the study of the SDS-TWR algorithm and its major error sources, such as those due to digital clock drift, among others. A preamble based on Frank-Zadoff-Chu sequence was developed and, due to its good periodic autocorrelation properties, a system employing the transmission and reception of this preamble was implemented in hardware, through a field programmable gate array (FPGA). By employing an embedded logic processor, the Altera Nios II, control over the complete procedure of the aforementioned algorithm is possible, to perform and analyze the main advantages of the SDS-TWR algorithm. Finally, a medium access control (MAC) layer frame format was defined, in order to enable future development of communication among multiple nodes, to enhance the original algorithm and, as such, provide the capability of trilateration

Design of Cloud Robotic Services for Senior Citizens to Improve Independent Living and Personal Health Management

A cloud robotics solution was designed and initially tested with a mobile robotic platform and a smart environment, in order to provide health-care management services to senior citizens and improve their independent living. The solution was evaluated in terms of Quality of Service (QoS) and tested in the realistic scenario of the DomoCasa Living Lab, Peccioli, Italy. In particular, a medication reminding service, a remote home monitoring and a user indoor localization algorithm were outsourced in the cloud and provided to the robots, users and carers. The system acquired data from a smart environment and addressed the robot to the user for service delivery. Experiments showed a service's Reliability of Response at least of the 0.04 % and a Time of Response of the same order of magnitude of the processing time required by the user localization algorithm