A Low-power, Reachable, Wearable and Intelligent IoT Device for Animal Activity Monitoring

Along with the proliferation of mobile devices and wireless signal coverage, IoT devices, such as smart wristbands for monitoring its owner’s activity or sleep patterns, get great popularity. Wearable technology in human life has become quite useful due to the information given (sleep hours, heart rate, etc). However, wearables for animals does not give information about behaviour directly: they collect raw data that is sent to a server where, after a post-processing step, the behaviour is known. In this work, we present a smart IoT device that classifies different animal behaviours from the information obtained from on-board sensors using an embedded neural network running in the device. This information is uploaded to a server through a wireless sensor network based on Zigbee communication. The architecture of the device allows an easy assembly in a reduced dimension wearable case. The firmware allows a modular functionality by activating or deactivating modules independently, which improve the power efficiency of the device. The power consumption has been analyzed, allowing the 1Ah battery to work the system during several days. A novel localization and distance estimation technique (for 802.15.4 networks) is presented to recover a lost device in Do˜nana National Park with unidirectional antennas and log-normalization distance estimation over RSSI.Junta de Andalucía P12-TIC-1300Ministerio de Economía y Competitividad TEC2016-77785-

Modular E-Collar for animal telemetry: an animal-centered design proposal

Animal telemetry is a subject of great potential and scientific interest, but it shows design-dependent problems related to price, flexibility and customization, autonomy, integration of elements, and structural design. The objective of this paper is to provide solutions, from the application of design, to cover the niches that we discovered by reviewing the scientific literature and studying the market. The design process followed to achieve the objective involved a development based on methodologies and basic design approaches focused on the human experience and also that of the animal. We present a modular collar that distributes electronic components in several compartments, connected, and powered by batteries that are wirelessly recharged. Its manufacture is based on 3D printing, something that facilitates immediacy in adaptation and economic affordability. The modularity presented by the proposal allows for adapting the size of the modules to the components they house as well as selecting which specific modules are needed in a project. The homogeneous weight distribution is transferred to the comfort of the animal and allows for a better integration of the elements of the collar. This device substantially improves the current offer of telemetry devices for farming animals, thanks to an animal-centered design process

Non-Invasive Data Acquisition and IoT Solution for Human Vital Signs Monitoring: Applications, Limitations and Future Prospects

The rapid development of technology has brought about a revolution in healthcare stimulating a wide range of smart and autonomous applications in homes, clinics, surgeries and hospitals. Smart healthcare opens the opportunity for a qualitative advance in the relations between healthcare providers and end-users for the provision of healthcare such as enabling doctors to diagnose remotely while optimizing the accuracy of the diagnosis and maximizing the benefits of treatment by enabling close patient monitoring. This paper presents a comprehensive review of non-invasive vital data acquisition and the Internet of Things in healthcare informatics and thus reports the challenges in healthcare informatics and suggests future work that would lead to solutions to address the open challenges in IoT and non-invasive vital data acquisition. In particular, the conducted review has revealed that there has been a daunting challenge in the development of multi-frequency vital IoT systems, and addressing this issue will help enable the vital IoT node to be reachable by the broker in multiple area ranges. Furthermore, the utilization of multi-camera systems has proven its high potential to increase the accuracy of vital data acquisition, but the implementation of such systems has not been fully developed with unfilled gaps to be bridged. Moreover, the application of deep learning to the real-time analysis of vital data on the node/edge side will enable optimal, instant offline decision making. Finally, the synergistic integration of reliable power management and energy harvesting systems into non-invasive data acquisition has been omitted so far, and the successful implementation of such systems will lead to a smart, robust, sustainable and self-powered healthcare system

Development of a simulation tool for measurements and analysis of simulated and real data to identify ADLs and behavioral trends through statistics techniques and ML algorithms

openCon una popolazione di anziani in crescita, il numero di soggetti a rischio di patologia è in rapido aumento. Molti gruppi di ricerca stanno studiando soluzioni pervasive per monitorare continuamente e discretamente i soggetti fragili nelle loro case, riducendo i costi sanitari e supportando la diagnosi medica. Comportamenti anomali durante l'esecuzione di attività di vita quotidiana (ADL) o variazioni sulle tendenze comportamentali sono di grande importanza.With a growing population of elderly people, the number of subjects at risk of pathology is rapidly increasing. Many research groups are studying pervasive solutions to continuously and unobtrusively monitor fragile subjects in their homes, reducing health-care costs and supporting the medical diagnosis. Anomalous behaviors while performing activities of daily living (ADLs) or variations on behavioral trends are of great importance. To measure ADLs a significant number of parameters need to be considering affecting the measurement such as sensors and environment characteristics or sensors disposition. To face the impossibility to study in the real context the best configuration of sensors able to minimize costs and maximize accuracy, simulation tools are being developed as powerful means. This thesis presents several contributions on this topic. In the following research work, a study of a measurement chain aimed to measure ADLs and represented by PIRs sensors and ML algorithm is conducted and a simulation tool in form of Web Application has been developed to generate datasets and to simulate how the measurement chain reacts varying the configuration of the sensors. Starting from eWare project results, the simulation tool has been thought to provide support for technicians, developers and installers being able to speed up analysis and monitoring times, to allow rapid identification of changes in behavioral trends, to guarantee system performance monitoring and to study the best configuration of the sensors network for a given environment. The UNIVPM Home Care Web App offers the chance to create ad hoc datasets related to ADLs and to conduct analysis thanks to statistical algorithms applied on data. To measure ADLs, machine learning algorithms have been implemented in the tool. Five different tasks have been identified. To test the validity of the developed instrument six case studies divided into two categories have been considered. To the first category belong those studies related to: 1) discover the best configuration of the sensors keeping environmental characteristics and user behavior as constants; 2) define the most performant ML algorithms. The second category aims to proof the stability of the algorithm implemented and its collapse condition by varying user habits. Noise perturbation on data has been applied to all case studies. Results show the validity of the generated datasets. By maximizing the sensors network is it possible to minimize the ML error to 0.8%. Due to cost is a key factor in this scenario, the fourth case studied considered has shown that minimizing the configuration of the sensors it is possible to reduce drastically the cost with a more than reasonable value for the ML error around 11.8%. Results in ADLs measurement can be considered more than satisfactory.INGEGNERIA INDUSTRIALEopenPirozzi, Michel

SHELDON Smart habitat for the elderly.

An insightful document concerning active and assisted living under different perspectives: Furniture and habitat, ICT solutions and Healthcare

State-of-the-Art Sensors Technology in Spain 2015: Volume 1

This book provides a comprehensive overview of state-of-the-art sensors technology in specific leading areas. Industrial researchers, engineers and professionals can find information on the most advanced technologies and developments, together with data processing. Further research covers specific devices and technologies that capture and distribute data to be processed by applying dedicated techniques or procedures, which is where sensors play the most important role. The book provides insights and solutions for different problems covering a broad spectrum of possibilities, thanks to a set of applications and solutions based on sensory technologies. Topics include: • Signal analysis for spectral power • 3D precise measurements • Electromagnetic propagation • Drugs detection • e-health environments based on social sensor networks • Robots in wireless environments, navigation, teleoperation, object grasping, demining • Wireless sensor networks • Industrial IoT • Insights in smart cities • Voice recognition • FPGA interfaces • Flight mill device for measurements on insects • Optical systems: UV, LEDs, lasers, fiber optics • Machine vision • Power dissipation • Liquid level in fuel tanks • Parabolic solar tracker • Force sensors • Control for a twin roto

Wearable sensors networks for safety applications in industrial scenarios

Industrial contexts, and in particular the port areas, are very complex systems to be monitored and controlled due to the combined presence of vehicles and people. The port areas are the gateway between navigation and terrestrial transportation and are of great importance in transport logistics. Unfortunately, the management of port areas is quite complex because the safety of the workers must be always assured. Therefore, in such a context, a centralized control system for the monitoring and the prevention of risks is of particular importance. In this thesis, a real-time control system for the monitoring of people and vehicles in industrial areas is proposed. The proposed system is based on the Internet of Things paradigm, i.e. a network of “things” (such as sensors, tag RFID, actuators etc.) which can communicate and interact with each other within a shared IP addressing range, in order to share data and contribute to the management and development of advanced applications. Specifically, the thesis is focused on the design of a wearable sensors network based on RFID technology, and specifically on WISP sensors, for assuring the safety of the workers. In this network, wearable devices that can be inserted directly on the textile have been selected. Differently from conventional sensors, wearable sensors ensure a higher level of comfort, and provide higher electromagnetic performance. Furthermore, textile materials are easily available. Microstrips are good candidates for these applications because they mainly radiate perpendicularly to the planar structure, and their ground plane allows a good shielding on the body tissues. Therefore, I have designed specific antennas for RFID, that unlike the classical microstrip antennas have the radiating surface composed of several "side by side" conductive "threads of textile". Since the microwave model does not allow the design of an antenna with these characteristics with a good approximation, a specific microwave model for coupled lines has been designed. With this model, the specific antenna for RFID has been designed, with Jeans as substrate. The particular antenna’s substrate allows direct integration into garments, but since the wearable antennas are placed very close to the human body, biological issues which may arise on the human body from the use of these sensors have been analysed. The Specific Absorption Rate (SAR) has been considered and simulations have been conducted for evaluating the effects on the human body, and especially on the head, when irradiated with the electromagnetic waves generated by the wearable antenna realized with different materials. Dosimetric effects have been evaluated in function of the distance from the body, in order to define a safe distance for placing the antenna on the human body. The SAR has been evaluated also for full patches with different textile substrates, whose surface is larger than that of the proposed model of coupled lines. Therefore, if the SAR values evaluated for the full patch are satisfying, the SAR values for the model of coupled lines will surely be acceptable

Wearable sensors networks for safety applications in industrial scenarios

Industrial contexts, and in particular the port areas, are very complex systems to be monitored and controlled due to the combined presence of vehicles and people. The port areas are the gateway between navigation and terrestrial transportation and are of great importance in transport logistics. Unfortunately, the management of port areas is quite complex because the safety of the workers must be always assured. Therefore, in such a context, a centralized control system for the monitoring and the prevention of risks is of particular importance. In this thesis, a real-time control system for the monitoring of people and vehicles in industrial areas is proposed. The proposed system is based on the Internet of Things paradigm, i.e. a network of “things” (such as sensors, tag RFID, actuators etc.) which can communicate and interact with each other within a shared IP addressing range, in order to share data and contribute to the management and development of advanced applications. Specifically, the thesis is focused on the design of a wearable sensors network based on RFID technology, and specifically on WISP sensors, for assuring the safety of the workers. In this network, wearable devices that can be inserted directly on the textile have been selected. Differently from conventional sensors, wearable sensors ensure a higher level of comfort, and provide higher electromagnetic performance. Furthermore, textile materials are easily available. Microstrips are good candidates for these applications because they mainly radiate perpendicularly to the planar structure, and their ground plane allows a good shielding on the body tissues. Therefore, I have designed specific antennas for RFID, that unlike the classical microstrip antennas have the radiating surface composed of several "side by side" conductive "threads of textile". Since the microwave model does not allow the design of an antenna with these characteristics with a good approximation, a specific microwave model for coupled lines has been designed. With this model, the specific antenna for RFID has been designed, with Jeans as substrate. The particular antenna’s substrate allows direct integration into garments, but since the wearable antennas are placed very close to the human body, biological issues which may arise on the human body from the use of these sensors have been analysed. The Specific Absorption Rate (SAR) has been considered and simulations have been conducted for evaluating the effects on the human body, and especially on the head, when irradiated with the electromagnetic waves generated by the wearable antenna realized with different materials. Dosimetric effects have been evaluated in function of the distance from the body, in order to define a safe distance for placing the antenna on the human body. The SAR has been evaluated also for full patches with different textile substrates, whose surface is larger than that of the proposed model of coupled lines. Therefore, if the SAR values evaluated for the full patch are satisfying, the SAR values for the model of coupled lines will surely be acceptable

Signal Enhancement Strategies in Classical Electrochemiluminescence Techniques for Modern Biosensing

With the ascent of IT, and since Ashton has invented the term Internet of Things (IoT) in 1999, this future idea of connected machines that can do tasks and perform decision-control cycles without human input has become more and more attractive and is today an established future scenario. Obviously, in an IoT, “sensors for everything” are one crucial corner stone of its existence and Analytical chemistry can and must deliver them. While many challenges towards a functioning IoT remain, we are on the verge of its beginning. This can be also seen with “Analytics 4.0” in research and on the market, tending to more IT-connected, portable, easier-controllable and integrated solutions. The entrance of mobility in the health sector or Point-of-Care (POC) diagnostics trends are alike influencing biosensing. Whether in mobile solutions or lab- and clinical environments, versatile, powerful and easy-to-adapt detection strategies like Electrochemiluminescence (ECL) are an attractive option. The ECL molecules [Ru(bpy)3]2+ and luminol represent the most prominent and most abundantly investigated luminophores for ECL since Bard’s accomplishment to make ECL a well-known technique. Because both are also two of the most efficient ECL emitters that can be well-handled in bioanalysis, and are available on the market, they are still today frequently used in research and also commercial applications. To cope with current benchmarks of sensitive detection, however a combination with a certain signal enhancement strategy is recommended. Several different routes can here be employed and one option is dendrimers. PAMAM dendrimers can function as ECL coreactant in [Ru(bpy)3]2+-ECL via their amino groups and at the same time expose primary amino groups as possible bioconjugation elements. Exploring this multi-functionality of the dendrimers was investigated here. This was done on a model system employing PAMAM dendrimers with [Ru(bpy)3]2+-ECL together with biotin/streptavidin as biorecognition element and analyte, respectively. The dendrimer’s bi-functionality was successfully proven and a joint-role of a biorecognition element and a possible reporter function suggests an optimum application in homogeneous assays. A different toolset for ECL signal enhancement is offered by liposomes. Numerous signaling molecules can be encapsulated inside the inner cavity of these synthetic vesicles, while they provide protection from the environment and connection-functionality to probes via lipids and surface groups on the outside. That application was here explored, together with a newly synthesized luminol derivative obtained by a simple synthesis route from commercial starting materials and exhibiting a four times increased ECL efficiency versus standard luminol. That was necessary as a liposome enhancement was denied for the standard luminol through its poor aqueous solubility. The new m-carboxy luminol considerably improved this feature which allowed its own encapsulation in liposomes. The superior signal generation with this dual system was proven in a model sandwich hybridization assay which yielded a 150-times better detection performance than the equal fluorescence-based assay while being almost zero affected through matrices like serum, soil or river water. As such the good performance of luminol ECL together with liposomes for highly sensitive detection applications was demonstrated. A further necessary element with liposomal amplification, are surfactants to set free the signaling molecules. However, this case depicts only one example of a multitude of applications of surfactants in bioassays and biochemical methods. Hence, surfactants are commonly present solution constituents which also have to be considered in general with ECL because they can influence the ECL signals positively or negatively. This was further investigated for luminol ECL by exploring the effect of 13 different surfactants on the luminol ECL efficiency on four different electrode materials. A deeper understanding of the distinct effects was obtained by looking into ECL emission behavior, electrochemical effects, the surfaces and Chemiluminescence effects. After all, the revelation of a complicated mechanism that involves many contributing factors and as such directs signal quenching or enhancement is an important finding for assay design. In this way, the selection of a suitable surfactant is possible to exploit maximum reachable signal efficiencies. A combination of signal enhancement tools like a better ECL molecule derivative, dendrimers, liposomes or surfactants has proven to boost the ECL performance considerably. A further means of signal enhancement is offered via miniaturization, which also makes the detection method better suited towards common application as liquid handling and easier automation are on hand. This can be used for single ECL assays or combinations of different ECL reagents in one system for multi-detection. Different strategies for the miniaturization of an ECL readout-capable system were investigated, taking requirements for [Ru(bpy)3]2+ and luminol as ECL reporters into account. This includes materials, electrochemical demands and simple design. Here, ITO electrodes – while advantageous for luminol ECL could not convince with their performance in [Ru(bpy)3]2+-ECL. Alternatively, laser scribed graphene electrodes have shown to be promising candidates for a future miniaturized system encompassing both, luminol and [Ru(bpy)3]2+ as ECL systems. Ultimately, the different signal amplifying strategies, investigated in this work that can be applied standalone or combined, offer a great toolset for state-of-the-art ECL detection applications in research and also for possible commercial applications

Advanced Materials and Technologies in Nanogenerators

This reprint discusses the various applications, new materials, and evolution in the field of nanogenerators. This lays the foundation for the popularization of their broad applications in energy science, environmental protection, wearable electronics, self-powered sensors, medical science, robotics, and artificial intelligence