Intelligent Personal Assistants Solutions in Ubiquitous Environments in the Context of Internet of Things

Internet of Things (IoT) will create the opportunity to develop new types of businesses. Every tangible object, biologic or not, will be identified by a unique address, creating a common network composed by billions of devices. Those devices will have different requirements, creating the necessity of finding new mechanisms to satisfy the needs of all the entities within the network. This is one of the main problems that all the scientific community should address in order to make Internet of Things the Future Internet. Currently, IoT is used in a lot of projects involving Wireless Sensor Networks (WSNs). Sensors are generally cheap and small devices able to generate useful information from physical indicators. They can be used on smart home scenarios, or even on healthcare environments, turning sensors into useful devices to accomplish the goals of many use case scenarios. Sensors and other devices with some reasoning capabilities, like smart objects, can be used to create smart environments. The interaction between the objects in those scenarios and humans can be eased by the inclusion of Intelligent Personal Assistants (IPAs). Currently, IPAs have good reasoning capabilities, improving the assistance they give to their owners. Artificial intelligence (AI), new learning mechanisms, and the evolution assisted in speech technology also contributed to this improvement. The integration of IPAs in IoT scenarios can become a case of great success. IPAs will comprehend the behavior of their owners not only through direct interactions, but also by the interactions they have with other objects in the environment. This may create ubiquitous communication scenarios where humans act as passive elements, being adequately informed of all the aspects of interest that surrounds them. The communication between IPAs and other objects in their surrounding environment may use gateways for traffic forwarding. On ubiquitous environments devices can be mobile or static. For example, in smart home scenarios, objects are generally static, being always on the same position. In mobile health scenarios, objects can move from one place to another. To turn IPAs useful on all types of environments, static and mobile gateways should be developed. On this dissertation, a novel mobile gateway solution for an IPA platform inserted on an IoT context is proposed. A mobile health scenario was chosen. Then, a Body Sensor Network (BSN) is always monitoring a person, giving the real time feedback of his/her health status to another person responsible by him (designated caretaker). On this scenario, a mobile gateway is needed to forward the traffic between the BSN and the IPA of the caretaker. Therefore, the IPA is able to give warnings about the health status of the person under monitoring, in real time. The proposed system is evaluated, demonstrated, and validated through a prototype, where the more important aspects for IPAs and IoT networks are considered

Mitigating interference coexistence issues in wireless sensor networks

Wireless Sensor Networks (WSNs) comprise a collection of portable, wireless, interconnected sensors deployed over an area to monitor and report a variable of interest; example applications include wildlife monitoring and home automation systems. In order to cater for long network lifetimes without the need for regular maintenance, energy efficiency is paramount, alongside link reliability. To minimise energy consumption, WSN MAC protocols employ Clear Channel Assessment (CCA), to transmit and receive packets. For transmitting, CCA is used beforehand to determine if the channel is clear. For receiving, CCA is used to decide if the radio should wake up to receive an incoming transmission, or be left in a power efficient sleep state. Current CCA implementations cannot determine the device type occupying the media, leaving nodes unable to differentiate between WSN traffic and arbitrary interference from other devices, such as WiFi. This affects link performance as packet loss increases, and energy efficiency as the radio is idly kept in receive mode. To permit WSN deployments in these environments, it is necessary to be able to gauge the effect of interference. While tools exist to model and predict packet loss in these conditions, it is currently not possible to do the same for energy consumption. This would be beneficial, as parameters of the network could be tuned to meet lifetime and energy requirements. In this thesis, methods to predict energy consumption of WSN MAC protocols are presented. These are shown to accurately estimate the idle listening from environmental interference measurements. Further, in order to mitigate the effects of interference, it would be beneficial for a CCA check to determine the device type occupying the media. For example, transmitters may select back-off strategies depending on the observed channel occupier. Receivers could be made more efficient by ignoring all non-WSN traffic, staying awake only after detecting an incoming WSN transmission. P-DCCA is a novel method presented in this thesis to achieve this. Transmitters vary the output power of the radio while the packet is being sent. Receivers are able to identify signals with this characteristic power variation, enabling a P-DCCA check to reveal if the medium is currently occupied by WSN traffic or other interference. P-DCCA is implemented in a common WSN MAC protocol, and is shown to achieve high detection accuracy, and to improve energy efficiency and packet delivery in interference environments

Robust, Resilient Networked Communication in Challenged Environments

In challenged environments, digital communication infrastructure may be difficult or even impossible to access. This is especially true in rural and developing regions, as well as in any region during a time of political or environmental crisis. We advance the state of the art in wireless networking and security to design networks and applications that rapidly assess changing networking conditions to restore communication and provide local situational awareness. This dissertation examines new systems for responding to current and emerging needs for wireless networks. This work looks across the wireless ecosystem of widely deployed standards. We develop new tools to improve network assessment and to provide robust and reliable network communication. By incorporating new technological breakthroughs, such as the wide commercial success of Unmanned Aircraft Systems (UAS), we introduce novel methods and systems for existing wireless standards for these challenged networks. We assess how existing technologies and standards function in difficult environments: lacking end-end Internet connectivity, experiencing overload or other resource constraints, and operating in three dimensional space. Through this lens, we demonstrate how to optimize networks to serve marginalized communities outside of first world urban cities and make our networks resilient to natural and political crisis that threaten communication

An Anthology of Next-Generation WSNs and Transformative IoT Use-Cases

The Internet of Things (IoT) paradigm brought an ever-increasing dependence on low-power devices to collect sensor data and transmit that information to the cloud, placing greater demand on connectivity and lifespan. In response, rapid worldwide innovation demonstrates the trade-offs in processing, communication, and energy consumption with diverse approaches to low-power components, duty-cycle schemes, cost, and many other critical constraints for complex use-cases, such as track-and-trace (T&T). This work explores the central theme of low-power wireless sensor networks (WSNs) in the IoT and Industrial IoT (IIoT). A collection of publications evolves through the theme, from an IoT literature review to enabling densely-scalable WSNs for logistics & asset management (LAM). Next, this research enhances the WSN design by leveraging wake-up radio (WUR) and energy harvesting (EH) to achieve battery-free operation. Lastly, this work presents WSNs to improve visibility and control of airflow/microclimate management in potentially transformative IIoT use-cases, such as data centers and agriculture

Opportunistic data collection and routing in segmented wireless sensor networks

La surveillance régulière des opérations dans les aires de manoeuvre (voies de circulation et pistes) et aires de stationnement d'un aéroport est une tâche cruciale pour son fonctionnement. Les stratégies utilisées à cette fin visent à permettre la mesure des variables environnementales, l'identification des débris (FOD) et l'enregistrement des statistiques d'utilisation de diverses sections de la surface. Selon un groupe de gestionnaires et contrôleurs d'aéroport interrogés, cette surveillance est un privilège des grands aéroports en raison des coûts élevés d'acquisition, d'installation et de maintenance des technologies existantes. Les moyens et petits aéroports se limitent généralement à la surveillance de quelques variables environnementales et des FOD effectuée visuellement par l'homme. Cette dernière activité impose l'arrêt du fonctionnement des pistes pendant l'inspection. Dans cette thèse, nous proposons une solution alternative basée sur les réseaux de capteurs sans fil (WSN) qui, contrairement aux autres méthodes, combinent les propriétés de faible coût d'installation et maintenance, de déploiement rapide, d'évolutivité tout en permettant d'effectuer des mesures sans interférer avec le fonctionnement de l'aéroport. En raison de la superficie d'un aéroport et de la difficulté de placer des capteurs sur des zones de transit, le WSN se composerait d'une collection de sous-réseaux isolés les uns des autres et du puits. Pour gérer cette segmentation, notre proposition s'appuie sur l'utilisation opportuniste des véhicules circulants dans l'aéroport considérés alors comme un type spécial de nœud appelé Mobile Ubiquitous LAN Extension (MULE) chargé de collecter les données des sous-réseaux le long de son trajet et de les transférer vers le puits. L'une des exigences pour le déploiement d'un nouveau système dans un aéroport est qu'il cause peu ou pas d'interruption des opérations régulières. C'est pourquoi l'utilisation d'une approche opportuniste basé sur des MULE est privilégiée dans cette thèse. Par opportuniste, nous nous référons au fait que le rôle de MULE est joué par certains des véhicules déjà existants dans un aéroport et effectuant leurs déplacements normaux. Et certains nœuds des sous- réseaux exploiteront tout moment de contact avec eux pour leur transmettre les données à transférer ensuite au puits. Une caractéristique des MULEs dans notre application est qu'elles ont des trajectoires structurées (suivant les voies de circulation dans l'aéroport), en ayant éventuellement un contact avec l'ensemble des nœuds situés le long de leur trajet (appelés sous-puits). Ceci implique la nécessité de définir une stratégie de routage dans chaque sous-réseau, capable d'acheminer les données collectées des nœuds vers les sous-puits et de répartir les paquets de données entre eux afin que le temps en contact avec la MULE soit utilisé le plus efficacement possible. Dans cette thèse, nous proposons un protocole de routage remplissant ces fonctions. Le protocole proposé est nommé ACME (ACO-based routing protocol for MULE-assisted WSNs). Il est basé sur la technique d'Optimisation par Colonies de Fourmis. ACME permet d'assigner des nœuds à des sous-puits puis de définir les chemins entre eux, en tenant compte de la minimisation de la somme des longueurs de ces chemins, de l'équilibrage de la quantité de paquets stockés par les sous-puits et du nombre total de retransmissions. Le problème est défini comme une tâche d'optimisation multi-objectif qui est résolue de manière distribuée sur la base des actions des nœuds dans un schéma collaboratif. Nous avons développé un environnement de simulation et effectué des campagnes de calculs dans OMNeT++ qui montrent les avantages de notre protocole en termes de performances et sa capacité à s'adapter à une grande variété de topologies de réseaux.The regular monitoring of operations in both movement areas (taxiways and runways) and non-movement areas (aprons and aircraft parking spots) of an airport, is a critical task for its functioning. The set of strategies used for this purpose include the measurement of environmental variables, the identification of foreign object debris (FOD), and the record of statistics of usage for diverse sections of the surface. According to a group of airport managers and controllers interviewed by us, the wide monitoring of most of these variables is a privilege of big airports due to the high acquisition, installation and maintenance costs of most common technologies. Due to this limitation, smaller airports often limit themselves to the monitoring of environmental variables at some few spatial points and the tracking of FOD performed by humans. This last activity requires stopping the functioning of the runways while the inspection is conducted. In this thesis, we propose an alternative solution based on Wireless Sensor Network (WSN) which, unlike the other methods/technologies, combines the desirable properties of low installation and maintenance cost, scalability and ability to perform measurements without interfering with the regular functioning of the airport. Due to the large extension of an airport and the difficulty of placing sensors over transit areas, the WSN might result segmented into a collection of subnetworks isolated from each other and from the sink. To overcome this problem, our proposal relies on a special type of node called Mobile Ubiquitous LAN Extension (MULE), able to move over the airport surface, gather data from the subnetworks along its way and eventually transfer it to the sink. One of the main demands for the deployment of any new system in an airport is that it must have little or no interference with the regular operations. This is why the use of an opportunistic approach for the transfer of data from the subnetworks to the MULE is favored in this thesis. By opportunistic we mean that the role of MULE will be played by some of the typical vehicles already existing in an airport doing their normal displacements, and the subnetworks will exploit any moment of contact with them to forward data to the sink. A particular characteristic of the MULEs in our application is that they move along predefined structured trajectories (given by the layout of the airport), having eventual contact with the set of nodes located by the side of the road (so-called subsinks). This implies the need for a data routing strategy to be used within each subnetwork, able to lead the collected data from the sensor nodes to the subsinks and distribute the data packets among them so that the time in contact with the MULE is used as efficiently as possible. In this thesis, we propose a routing protocol which undertakes this task. Our proposed protocol is named ACME, standing for ACO-based routing protocol for MULE-assisted WSNs. It is founded on the well known Ant Colony Optimization (ACO) technique. The main advantage of ACO is its natural fit to the decentralized nature of WSN, which allows it to perform distributed optimizations (based on local interactions) leading to remarkable overall network performance. ACME is able to assign sensor nodes to subsinks and generate the corresponding multi-hop paths while accounting for the minimization of the total path length, the total subsink imbalance and the total number of retransmissions. The problem is defined as a multi-objective optimization task which is resolved in a distributed manner based on actions of the sensor nodes acting in a collaborative scheme. We conduct a set of computational experiments in the discrete event simulator OMNeT++ which shows the advantages of our protocol in terms of performance and its ability to adapt to a variety of network topologie

Cognitive Security Framework For Heterogeneous Sensor Network Using Swarm Intelligence

Rapid development of sensor technology has led to applications ranging from academic to military in a short time span. These tiny sensors are deployed in environments where security for data or hardware cannot be guaranteed. Due to resource constraints, traditional security schemes cannot be directly applied. Unfortunately, due to minimal or no communication security schemes, the data, link and the sensor node can be easily tampered by intruder attacks. This dissertation presents a security framework applied to a sensor network that can be managed by a cohesive sensor manager. A simple framework that can support security based on situation assessment is best suited for chaotic and harsh environments. The objective of this research is designing an evolutionary algorithm with controllable parameters to solve existing and new security threats in a heterogeneous communication network. An in-depth analysis of the different threats and the security measures applied considering the resource constrained network is explored. Any framework works best, if the correlated or orthogonal performance parameters are carefully considered based on system goals and functions. Hence, a trade-off between the different performance parameters based on weights from partially ordered sets is applied to satisfy application specific requirements and security measures. The proposed novel framework controls heterogeneous sensor network requirements,and balance the resources optimally and efficiently while communicating securely using a multi-objection function. In addition, the framework can measure the affect of single or combined denial of service attacks and also predict new attacks under both cooperative and non-cooperative sensor nodes. The cognitive intuition of the framework is evaluated under different simulated real time scenarios such as Health-care monitoring, Emergency Responder, VANET, Biometric security access system, and Battlefield monitoring. The proposed three-tiered Cognitive Security Framework is capable of performing situation assessment and performs the appropriate security measures to maintain reliability and security of the system. The first tier of the proposed framework, a crosslayer cognitive security protocol defends the communication link between nodes during denial-of-Service attacks by re-routing data through secure nodes. The cognitive nature of the protocol balances resources and security making optimal decisions to obtain reachable and reliable solutions. The versatility and robustness of the protocol is justified by the results obtained in simulating health-care and emergency responder applications under Sybil and Wormhole attacks. The protocol considers metrics from each layer of the network model to obtain an optimal and feasible resource efficient solution. In the second tier, the emergent behavior of the protocol is further extended to mine information from the nodes to defend the network against denial-of-service attack using Bayesian models. The jammer attack is considered the most vulnerable attack, and therefore simulated vehicular ad-hoc network is experimented with varied types of jammer. Classification of the jammer under various attack scenarios is formulated to predict the genuineness of the attacks on the sensor nodes using receiver operating characteristics. In addition to detecting the jammer attack, a simple technique of locating the jammer under cooperative nodes is implemented. This feature enables the network in isolating the jammer or the reputation of node is affected, thus removing the malicious node from participating in future routes. Finally, a intrusion detection system using `bait\u27 architecture is analyzed where resources is traded-off for the sake of security due to sensitivity of the application. The architecture strategically enables ant agents to detect and track the intruders threateningthe network. The proposed framework is evaluated based on accuracy and speed of intrusion detection before the network is compromised. This process of detecting the intrusion earlier helps learn future attacks, but also serves as a defense countermeasure. The simulated scenarios of this dissertation show that Cognitive Security Framework isbest suited for both homogeneous and heterogeneous sensor networks

Pyöräilyn ympäristötekijöiden mittaaminen esineiden internetin sovelluksia varten

Increasing population in cities creates increasing amount of traffic, which leads to emissions and traffic congestion. Smart Cities set out to solve the challenges urban cities face due to the increased population, using Internet of Things as means to monitor the assets as it allows non-traditional devices to connect as a part of global information network. At the same time, cycling has increased its popularity as an environmentally friendly as well as healthy transportation method. To further its usage, infrastructure in cities must support cycling as a serious transportation method. For this purpose, it is important to include bicycles to Smart City with measurements of cycling and its environment. This thesis studies if it is possible to measure factors affecting cycling environment and assess route quality without using sensors built in bicycle frame. Decision to avoid sensors embedded in frame stemmed from incentive to have easily available and inexpensive measuring device, which does not bind the cyclists to use bicycles from specific brand or require them to purchase new bike if they are interested in participating in measuring. For evaluating the feasibility of cycling environment measuring, prototype called BikeBox was built and used during test drives. In addition, an online survey was held, which received answers from 97 cyclists. The survey queried about their cycling habits and preferences to better understand what kind of data they would be interested in. The prototype included accelerometer for measuring road quality, photoresistor to identify poorly lit areas and GPS module for location and timestamps, which are needed for other measurements as well as finding possible stopping points and slow areas on the route. Based on the test drives it is possible to identify quality changes on road surface as well as changes in lighting. Inaccurate GPS positioning does pose a challenge for pinpointing exact locations, though. Using location and timestamps it is possible to calculate the speed along different parts of the route, including areas which cause interruptions for the cyclists. This thesis presents results from 7 different example drives, though during testing phase more test driving was done. To get comprehensive coverage, crowdsourcing should be considered as the data gathering method. Based on the survey fastness and length of the route, amount of stops and interruptions and road condition are one of the most important factors for the cyclists. When queried what kind of information cyclists would like to receive, the road condition related factors were most commonly mentioned.Kaupungistumisen seurauksena väkimäärät kaupungeissa kasvavat, mikä tuo mukanaan kasvavat liikennemäärät, ruuhkat ja liikennepäästöt. Älykkäät kaupungit ovat reaktio kaupungistumisesta seuraaviin haasteisiin. Älykkäät kaupungit pyrkivät seuraamaan ja kontrolloimaan kaupungin infrastruktuuria, apunaan esineiden internet. Esineiden internet mahdollistaa epäperinteisten laitteiden yhdistämisen maailmanlaajuiseen tietoverkkoon. Samaan aikaan pyöräilyn suosio on kasvanut ympäristöystävällisenä ja terveellisenä liikennemuotona. Jos pyöräilyn määrää halutaan jatkossakin kasvattaa, kaupungin infrastruktuurin täytyy tukea pyöräilyä vakavasti otettavana liikennemuotona. Jotta tämä voidaan saavuttaa, on pyöräilijöiden pyöräily-ympäristön ja pyöräilytapojen ymmärtäminen tärkeää. Tässä työssä tutkitaan, onko pyöräily-ympäristöön vaikuttavia tekijöitä mahdollista mitata sensoreilla, joita ei ole istutettu polkupyörän runkoon. Runkoon upotettuja sensoreita haluttiin välttää, jotta mittauslaitteet voisivat olla mahdollisimman suuren joukon saatavilla, eikä pyöräilijä olisi sidottu käyttämään tietyn valmistajan polkupyörää. Lisäksi pyritään selvittämään, minkälaisesta pyöräily-ympäristöön liittyvästä datasta pyöräilijät olisivat kiinnostuneita. Tähän tarkoitukseen rakennettiin prototyyppi PyöräPurkista (BikeBox). Lisäksi toteutettiin internet-kysely, johon vastasi 97 polkupyöräilijää. Kyselyllä selvitettiin pyöräilijöiden pyöräilytapoja ja -mieltymyksiä ja sitä, millainen pyöräily-ympäristöstä kertova data kiinnostaisi heitä. Prototyyppiin sisällytettiin kiihtyvyysanturi tien pinnan laadun mittaamiseen, valoanturi heikosti valaistujen alueiden tunnistamiseen ja GPS-moduuli, jolla saadaan sijantitieto ja kellonaika muita mittauksia varten. Lisäksi sijaintitiedosta ja kellonajasta voidaan laskea ajonopeus ja paikat, missä pyöräilijä on joutunut keskeyttämään ajonsa. Testiajojen perusteella on mahdollista havaita tien pinnanlaadun muutos sekä muutos valaistusolosuhteissa. Epätarkkuudet GPS-paikannuksessa vaikeuttavat kuitenkin ongelmakohtien tarkkaa paikallistamista. Tämä työ käsittelee aiheita 7 erillisen testiajon kautta, vaikka testausvaiheessa ajettiinkin useampia testiajoja. Kattavien mittausten saamiseksi joukkoistamista kannattaisi harkita datankeräysmetodina. Tehdyn kyselyn perusteella reitin nopeus, pituus, reitillä olevien keskeytysten määrä ja tien kunto ovat tärkeimpiä reitin laatuun vaikuttavia tekijöitä. Erilaiset pyöräilyreitin kuntoon liittyvät asiat kiinnostivat eniten kun kysyttiin, minkälaista dataa pyöräilijät haluaisivat saada

Enhancing the security of wireless sensor network based home automation systems

Home automation systems (HASs)seek to improve the quality of life for individuals through the automation of household devices. Recently, there has been a trend, in academia and industry, to research and develop low-cost Wireless Sensor Network (WSN) based HASs (Varchola et al. 2007). WSNs are designed to achieve a low-cost wireless networking solution, through the incorporation of limited processing, memory, and power resources. Consequently, providing secure and reliable remote access for resource limited WSNs, such as WSN based HASs, poses a significant challenge (Perrig et al. 2004). This thesis introduces the development of a hybrid communications approach to increase the resistance of WSN based HASs to remote DoS flooding attacks targeted against a third party. The approach is benchmarked against the dominant GHS remote access approach for WSN based HASs (Bergstrom et al. 2001), on a WSN based HAS test-bed, and shown to provide a minimum of a 58.28%, on average 59.85%, and a maximum of 61.45% increase in remote service availability during a DoS attack. Additionally, a virtual home incorporating a cryptographic based DoS detection algorithm, is developed to increase resistance to remote DoS flooding attacks targeted directly at WSN based HASs. The approach is benchmarked against D-WARD (Mirkovic 2003), the most effective DoS defence identified from the research, and shown to provide a minimum 84.70%, an average 91.13% and a maximum 95.6% reduction in packets loss on a WSN based HAS during a DoS flooding attack. Moreover, the approach is extended with the integration of a virtual home, hybrid communication approach, and a distributed denial of defence server to increase resistance to remote DoS attacks targeting the home gateway. The approach is again benchmarked against the D-WARD defence and shown to decrease the connection latency experienced by remote users by a minimum of 90.14%, an average 90.90%, and a maximum 91.88%.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Exploring the potential of dynamic mode decomposition in wireless communication and neuroscience applications

The exponential growth of available experimental, simulation, and historical data from modern systems, including those typically considered divergent (e.g., Neuroscience procedures and wireless networks), has created a persistent need for effective data mining and analysis techniques. Most systems can be characterized as high-dimensional, dynamical, exhibiting rich multiscale phenomena in both space and time. Engineering studies of complex linear and non-linear dynamical systems are especially challenging, as the behavior of the system is often unknown and complex. Studying this problem of interest necessitates discovering and modeling the underlying evolving dynamics. In such cases, a simplified, predictive model of the flow evolution profile must be developed based on observations/measurements collected from the system. Consequently, data-driven algorithms have become an essential tool for modeling and analyzing complex systems characterized by high nonlinearity and dimensionality. The field of data-driven modeling and analysis of complex systems is rapidly advancing. Associated investigations are poised to revolutionize the engineering, biomedical, and physical sciences. By applying modeling techniques, a complex system can be simplified using low-dimensional models with spatial-temporal structures described using system measurements. Such techniques enable complex system modeling without requiring knowledge of dynamic equations governing the system's operation. The primary objective of the work detailed in this dissertation was characterizing, identifying, and predicting the behavior of systems under analysis. In particular, characterization and identification entailed finding patterns embedded in system data; prediction required evaluating system dynamics. The thesis of this work proposes the implementation of dynamic mode decomposition (DMD), which is a fully data-driven technique, to characterize dynamical systems from extracted measurements. DMD employs singular value decomposition (SVD), which reduces high-dimensional measurements collected from a system and computes eigenvalues and eigenvectors of a linear approximated model. In other words, by rather estimating the underlying dynamics within a system, DMD serves as a powerful tool for system characterization without requiring knowledge of the governing dynamical equations. Overall, the work presented herein demonstrates the potential of DMD for analyzing and modeling complex systems in the emerging, synthesized field of wireless communication (i.e., wireless technology identification) and neuroscience (i.e., chemotherapy-induced peripheral neuropathy [CIPN] identification for cancer patients). In the former, a novel technique based on DMD was initially developed for wireless coexistence analysis. The scheme can differentiate various wireless technologies, including GSM and LTE signals in the cellular domain and IEEE802.11n, ac, and ax in the Wi-Fi domain, as well as Bluetooth and Zigbee in the personal wireless domain. By capturing embedded periodic features transmitted within the signal, the proposed DMD-based technique can identify a signal’s time domain signature. With regard to cancer neuroscience, a DMD-based scheme was developed to capture the pattern of plantar pressure variability due to the development of neuropathy resulting from neurotoxic chemotherapy treatment. The developed technique modeled gait pressure variations across multiple steps at three plantar regions, which characterized the development of CIPN in patients with uterine cancer. Obtained results demonstrated that DMD can effectively model various systems and characterize system dynamics. Given the advantages of fast data processing, minimal required data preprocessing, and minimal required signal observation time intervals, DMD has proven to be a powerful tool for system analysis and modeling