Internet of things in health: Requirements, issues, and gaps

Background and objectives: The Internet of Things (IoT) paradigm has been extensively applied to several sectors in the last years, ranging from industry to smart cities. In the health domain, IoT makes possible new scenarios of healthcare delivery as well as collecting and processing health data in real time from sensors in order to make informed decisions. However, this domain is complex and presents several tech- nological challenges. Despite the extensive literature about this topic, the application of IoT in healthcare scarcely covers requirements of this sector. Methods: A literature review from January 2010 to February 2021 was performed resulting in 12,108 articles. After filtering by title, abstract, and content, 86 were eligible and examined according to three requirement themes: data lifecycle; trust, security, and privacy; and human-related issues. Results: The analysis of the reviewed literature shows that most approaches consider IoT application in healthcare merely as in any other domain (industry, smart cities…), with no regard of the specific requirements of this domain. Conclusions: Future effort s in this matter should be aligned with the specific requirements and needs of the health domain, so that exploiting the capabilities of the IoT paradigm may represent a meaningful step forward in the application of this technology in healthcare.Consejería de Conocimiento, Investigación y Universidad, Junta de Andalucía P18-TPJ - 307

A cross-layer approach for optimizing the efficiency of wireless sensor and actor networks

Recent development has lead to the emergence of distributed Wireless Sensor and Actor Networks (WSAN), which are capable of observing the physical environment, processing the data, making decisions based on the observations and performing appropriate actions. WSANs represent an important extension of Wireless Sensor Networks (WSNs) and may comprise a large number of sensor nodes and a smaller number of actor nodes. The sensor nodes are low-cost, low energy, battery powered devices with restricted sensing, computational and wireless communication capabilities. Actor nodes are resource richer with superior processing capabilities, higher transmission powers and a longer battery life. A basic operational scenario of a typical WSAN application follows the following sequence of events. The physical environment is periodically sensed and evaluated by the sensor nodes. The sensed data is then routed towards an actor node. Upon receiving sensed data, an actor node performs an action upon the physical environment if necessary, i.e. if the occurrence of a disturbance or critical event has been detected. The specific characteristics of sensor and actor nodes combined with some stringent application constraints impose unique requirements for WSANs. The fundamental challenges for WSANs are to achieve low latency, high energy efficiency and high reliability. The latency and energy efficiency requirements are in a trade-off relationship. The communication and coordination inside WSANs is managed via a Communication Protocol Stack (CPS) situated on every node. The requirements of low latency and energy efficiency have to be addressed at every layer of the CPS to ensure overall feasibility of the WSAN. Therefore, careful design of protocol layers in the CPS is crucial in attempting to meet the unique requirements and handle the abovementioned trade-off relationship in WSANs. The traditional CPS, comprising the application, network, medium access control and physical layer, is a layered protocol stack with every layer, a predefined functional entity. However, it has been found that for similar types of networks with similar stringent network requirements, the strictly layered protocol stack approach performs at a sub-optimal level with regards to network efficiency. A modern cross-layer paradigm, which proposes the employment of interactions between layers in the CPS, has recently attracted a lot of attention. The cross-layer approach promotes network efficiency optimization and promises considerable performance gains. It is found that in literature, the adoption of this cross-layer paradigm has not yet been considered for WSANs. In this dissertation, a complete cross-layer enabled WSAN CPS is developed that features the adoption of the cross-layer paradigm towards promoting optimization of the network efficiency. The newly proposed cross-layer enabled CPS entails protocols that incorporate information from other layers into their local decisions. Every protocol layer provides information identified as beneficial to another layer(s) in the CPS via a newly proposed Simple Cross-Layer Framework (SCLF) for WSANs. The proposed complete cross-layer enabled WSAN CPS comprises a Cross-Layer enabled Network-Centric Actuation Control with Data Prioritization (CL-NCAC-DP) application layer (APPL) protocol, a Cross-Layer enabled Cluster-based Hierarchical Energy/Latency-Aware Geographic Routing (CL-CHELAGR) network layer (NETL) protocol and a Cross-Layer enabled Carrier Sense Multiple Access with Minimum Preamble Sampling and Duty Cycle Doubling (CL-CSMA-MPS-DCD) medium access control layer (MACL) protocol. Each of these protocols builds on an existing simple layered protocol that was chosen as a basis for development of the cross-layer enabled protocols. It was found that existing protocols focus primarily on energy efficiency to ensure maximum network lifetime. However, most WSAN applications require latency minimization to be considered with the same importance. The cross-layer paradigm provides means of facilitating the optimization of both latency and energy efficiency. Specifically, a solution to the latency versus energy trade-off is given in this dissertation. The data generated by sensor nodes is prioritised by the APPL and depending on the delay-sensitivity, handled in a specialised manor by every layer of the CPS. Delay-sensitive data packets are handled in order to achieve minimum latency. On the other hand, delay-insensitive non critical data packets are handled in such a way as to achieve the highest energy efficiency. In effect, either latency minimization or energy efficiency receives an elevated precedence according to the type of data that is to be handled. Specifically, the cross-layer enabled APPL protocol provides information pertaining to the delay-sensitivity of sensed data packets to the other layers. Consequently, when a data packet is detected as highly delay-sensitive, the cross-layer enabled NETL protocol changes its approach from energy efficient routing along the maximum residual energy path to routing along the fastest path towards the cluster-head actor node for latency minimizing of the specific packet. This is done by considering information (contained in the SCLF neighbourhood table) from the MACL that entails wakeup schedules and channel utilization at neighbour nodes. Among the added criteria, the next-hop node is primarily chosen based on the shortest time to wakeup. The cross-layer enabled MACL in turn employs a priority queue and a temporary duty cycle doubling feature to enable rapid relaying of delay-sensitive data. Duty cycle doubling is employed whenever a sensor node’s APPL state indicates that it is part of a critical event reporting route. When the APPL protocol state (found in the SCLF information pool) indicates that the node is not part of the critical event reporting route anymore, the MACL reverts back to promoting energy efficiency by disengaging duty cycle doubling and re-employing a combination of a very low duty cycle and preamble sampling. The APPL protocol conversely considers the current queue size of the MACL and temporarily halts the creation of data packets (only if the sensed value is non critical) to prevent a queue overflow and ease congestion at the MACL By simulation it was shown that the cross-layer enabled WSAN CPS consistently outperforms the layered CPS for various network conditions. The average end-to-end latency of delay-sensitive critical data packets is decreased substantially. Furthermore, the average end-to-end latency of delay-insensitive data packets is also decreased. Finally, the energy efficiency performance is decreased by a tolerable insignificant minor margin as expected. The trivial increase in energy consumption is overshadowed by the high margin of increase in latency performance for delay-sensitive critical data packets. The newly proposed cross-layer CPS achieves an immense latency performance increase for WSANs, while maintaining excellent energy efficiency. It has hence been shown that the adoption of the cross-layer paradigm by the WSAN CPS proves hugely beneficial with regards to the network efficiency performance. This increases the feasibility of WSANs and promotes its application in more areas.Dissertation (MEng)--University of Pretoria, 2009.Electrical, Electronic and Computer Engineeringunrestricte

CPS Data Streams Analytics based on Machine Learning for Cloud and Fog Computing: A Survey

Cloud and Fog computing has emerged as a promising paradigm for the Internet of things (IoT) and cyber-physical systems (CPS). One characteristic of CPS is the reciprocal feedback loops between physical processes and cyber elements (computation, software and networking), which implies that data stream analytics is one of the core components of CPS. The reasons for this are: (i) it extracts the insights and the knowledge from the data streams generated by various sensors and other monitoring components embedded in the physical systems; (ii) it supports informed decision making; (iii) it enables feedback from the physical processes to the cyber counterparts; (iv) it eventually facilitates the integration of cyber and physical systems. There have been many successful applications of data streams analytics, powered by machine learning techniques, to CPS systems. Thus, it is necessary to have a survey on the particularities of the application of machine learning techniques to the CPS domain. In particular, we explore how machine learning methods should be deployed and integrated in cloud and fog architectures for better fulfilment of the requirements, e.g. mission criticality and time criticality, arising in CPS domains. To the best of our knowledge, this paper is the first to systematically study machine learning techniques for CPS data stream analytics from various perspectives, especially from a perspective that leads to the discussion and guidance of how the CPS machine learning methods should be deployed in a cloud and fog architecture

Application of cognitive radio based sensor network in smart grids for efficient, holistic monitoring and control.

Doctoral Degree. University of KwaZulu-Natal, Durban.This thesis is directed towards the application of cognitive radio based sensor network (CRSN) in smart grid (SG) for efficient, holistic monitoring and control. The work involves enabling of sensor network and wireless communication devices for spectra utilization via the capability of Dynamic Spectrum Access (DSA) of a cognitive radio (CR) as well as end to end communication access technology for unified monitoring and control in smart grids. Smart Grid (SG) is a new power grid paradigm that can provide predictive information and recommendations to utilities, including their suppliers, and their customers on how best to manage power delivery and consumption. SG can greatly reduce air pollution from our surrounding by renewable power sources such as wind energy, solar plants and huge hydro stations. SG also reduces electricity blackouts and surges. Communication network is the foundation for modern SG. Implementing an improved communication solution will help in addressing the problems of the existing SG. Hence, this study proposed and implemented improved CRSN model which will help to ultimately evade the inherent problems of communication network in the SG such as: energy inefficiency, interference, spectrum inefficiencies, poor quality of service (QoS), latency and throughput. To overcome these problems, the existing approach which is more predominant is the use of wireless sensor network (WSNs) for communication needs in SG. However, WSNs have low battery power, low computational complexity, low bandwidth support, and high latency or delay due to multihop transmission in existing WSN topology. Consequently, solving these problems by addressing energy efficiency, bandwidth or throughput, and latency have not been fully realized due to the limitations in the WSN and the existing network topology. Therefore, existing approach has not fully addressed the communication needs in SG. SG can be fully realized by integrating communication network technologies infrastructures into the power grid. Cognitive Radio-based Sensor Network (CRSN) is considered a feasible solution to enhance various aspects of the electric power grid such as communication with end and remote devices in real-time manner for efficient monitoring and to realize maximum benefits of a smart grid system. CRSN in SG is aimed at addressing the problem of spectrum inefficiency and interference which wireless sensor network (WSN) could not. However, numerous challenges for CRSNs are due to the harsh environmental wireless condition in a smart grid system. As a result, latency, throughput and reliability become critical issues. To overcome these challenges, lots of approaches can be adopted ranging from integration of CRSNs into SGs; proper implementation design model for SG; reliable communication access devices for SG; key immunity requirements for communication infrastructure in SG; up to communication network protocol optimization and so on. To this end, this study utilized the National Institute of Standard (NIST) framework for SG interoperability in the design of unified communication network architecture including implementation model for guaranteed quality of service (QoS) of smart grid applications. This involves virtualized network in form of multi-homing comprising low power wide area network (LPWAN) devices such as LTE CAT1/LTE-M, and TV white space band device (TVBD). Simulation and analysis show that the performance of the developed modules architecture outperforms the legacy wireless systems in terms of latency, blocking probability, and throughput in SG harsh environmental condition. In addition, the problem of multi correlation fading channels due to multi antenna channels of the sensor nodes in CRSN based SG has been addressed by the performance analysis of a moment generating function (MGF) based M-QAM error probability over Nakagami-q dual correlated fading channels with maximum ratio combiner (MRC) receiver technique which includes derivation and novel algorithmic approach. The results of the MATLAB simulation are provided as a guide for sensor node deployment in order to avoid the problem of multi correlation in CRSN based SGs. SGs application requires reliable and efficient communication with low latency in timely manner as well as adequate topology of sensor nodes deployment for guaranteed QoS. Another important requirement is the need for an optimized protocol/algorithms for energy efficiency and cross layer spectrum aware made possible for opportunistic spectrum access in the CRSN nodes. Consequently, an optimized cross layer interaction of the physical and MAC layer protocols using various novel algorithms and techniques was developed. This includes a novel energy efficient distributed heterogeneous clustered spectrum aware (EDHC- SA) multichannel sensing signal model with novel algorithm called Equilateral triangulation algorithm for guaranteed network connectivity in CRSN based SG. The simulation results further obtained confirm that EDHC-SA CRSN model outperforms conventional ZigBee WSN in terms of bit error rate (BER), end-to-end delay (latency) and energy consumption. This no doubt validates the suitability of the developed model in SG

Wireless sensor network as a distribute database

Wireless sensor networks (WSN) have played a role in various fields. In-network data processing is one of the most important and challenging techniques as it affects the key features of WSNs, which are energy consumption, nodes life circles and network performance. In the form of in-network processing, an intermediate node or aggregator will fuse or aggregate sensor data, which are collected from a group of sensors before transferring to the base station. The advantage of this approach is to minimize the amount of information transferred due to lack of computational resources. This thesis introduces the development of a hybrid in-network data processing for WSNs to fulfil the WSNs constraints. An architecture for in-network data processing were proposed in clustering level, data compression level and data mining level. The Neighbour-aware Multipath Cluster Aggregation (NMCA) is designed in the clustering level, which combines cluster-based and multipath approaches to process different packet loss rates. The data compression schemes and Optimal Dynamic Huffman (ODH) algorithm compressed data in the cluster head for the compressed level. A semantic data mining for fire detection was designed for extracting information from the raw data by the semantic data-mining model is developed to improve data accuracy and extract the fire event in the simulation. A demo in-door location system with in-network data processing approach is built to test the performance of the energy reduction of our designed strategy. In conclusion, the added benefits that the technical work can provide for in-network data processing is discussed and specific contributions and future work are highlighted

Heterogeneous and opportunistic wireless networks

Recent years have witnessed the evolution of a large plethora of wireless technologies with different characteristics, as a response of the operators' and users' needs in terms of an efficient and ubiquitous delivery of advanced multimedia services. The wireless segment of network infrastructure has penetrated in our lives, and wireless connectivity has now reached a state where it is considered to be an indispensable service as electricity or water supply. Wireless data networks grow increasingly complex as a multiplicity of wireless information terminals with sophisticated capabilities get embedded in the infrastructure. © 2012 Springer Milan. All Right Reserved

Urubu: energy scavenging in wireless sensor networks

For the past years wireless sensor networks (WSNs) have been coined as one of the most promising technologies for supporting a wide range of applications. However, outside the research community, few are the people who know what they are and what they can offer. Even fewer are the ones that have seen these networks used in real world applications. The main obstacle for the proliferation of these networks is energy, or the lack of it. Even though renewable energy sources are always present in the networks environment, designing devices that can efficiently scavenge that energy in order to sustain the operation of these networks is still an open challenge. Energy scavenging, along with energy efficiency and energy conservation, are the current available means to sustain the operation of these networks, and can all be framed within the broader concept of “Energetic Sustainability”. A comprehensive study of the several issues related to the energetic sustainability of WSNs is presented in this thesis, with a special focus in today’s applicable energy harvesting techniques and devices, and in the energy consumption of commercially available WSN hardware platforms. This work allows the understanding of the different energy concepts involving WSNs and the evaluation of the presented energy harvesting techniques for sustaining wireless sensor nodes. This survey is supported by a novel experimental analysis of the energy consumption of the most widespread commercially available WSN hardware platforms.Há já alguns anos que as redes de sensores sem fios (do Inglês Wireless Sensor Networks - WSNs) têm sido apontadas como uma das mais promissoras tecnologias de suporte a uma vasta gama de aplicações. No entanto, fora da comunidade científica, poucas são as pessoas que sabem o que elas são e o que têm para oferecer. Ainda menos são aquelas que já viram a sua utilização em aplicações do dia-a-dia. O principal obstáculo para a proliferação destas redes é a energia, ou a falta dela. Apesar da existência de fontes de energia renováveis no local de operação destas redes, continua a ser um desafio construir dispositivos capazes de aproveitar eficientemente essa energia para suportar a operação permanente das mesmas. A colheita de energia juntamente com a eficiência energética e a conservação de energia, são os meios disponíveis actualmente que permitem a operação permanente destas redes e podem ser todos englobados no conceito mais amplo de “Sustentabilidade Energética”. Esta tese apresenta um estudo extensivo das várias questões relacionadas com a sustentabilidade energética das redes de sensores sem fios, com especial foco nas tecnologias e dispositivos explorados actualmente na colheita de energia e no consumo energético de algumas plataformas comercias de redes de sensores sem fios. Este trabalho permite compreender os diferentes conceitos energéticos relacionados com as redes de sensores sem fios e avaliar a capacidade das tecnologias apresentadas em suportar a operação permanente das redes sem fios. Este estudo é suportado por uma inovadora análise experimental do consumo energético de algumas das mais difundidas plataformas comerciais de redes de sensores sem fios