DIEstro: Motion sensor platform for cattle oestrus detection

The reproductive efficiency of dairy industry has decreased over the last ten years due mainly to an intensification of the management techniques of the herd, and an increase of total number of animals. A main objective of worldwide dairy farms is to ensure that dairy cows, produce as much milk as possible. A cow produces milk while it has a calf to breastfeed, therefore, the less time passes between births, the more ”productive” the cows are. This is the principal reason why the precise heat (oestrus) detection has became so important, a task traditionally assigned to veterinary and expert people examining and watching the cattle behavior, and in recent years to electronic devices monitoring the cow’s physical activity. Tracking the animal’s physical activity by means of a portable device strapped to each animal, is known to be a very effective way to determine heat, but sometimes requires expensive hardware and large batteries. In this work, a low-cost micropower wireless system able to automatically detect oestrus period of cattle is presented. It was designed in cooperation with BQN, a company developing technology for the agribusiness industry in Uruguay. The tracker seizes the recent availability of 1 uA micropower accelerometers, LoRa long range transceivers, and FRAM microcontrollers, to achieve a coin cell battery powered paradigm for oestrus detection. The device records 3 axis acceleration information, process it, and periodically sends it to a server; it has a measured ultra low power consumption of 4 uA while collecting/processing data, reaching a very large (> 10km) communication distance using a star topology and LoRa technology at countryside areas. The scope of the project and this documentation is the entire hardware and firmware development, from the start idea, design and final implementation.Agencia Nacional de Investigación e Innovació

DIEstro: Motion sensor platform for cattle oestrus detection

The reproductive efficiency of dairy industry has decreased over the last ten years due mainly to an intensification of the management techniques of the herd, and an increase of total number of animals. A main objective of worldwide dairy farms is to ensure that dairy cows, produce as much milk as possible. A cow produces milk while it has a calf to breastfeed, therefore, the less time passes between births, the more ”productive” the cows are. This is the principal reason why the precise heat (oestrus) detection has became so important, a task traditionally assigned to veterinary and expert people examining and watching the cattle behavior, and in recent years to electronic devices monitoring the cow’s physical activity. Tracking the animal’s physical activity by means of a portable device strapped to each animal, is known to be a very effective way to determine heat, but sometimes requires expensive hardware and large batteries. In this work, a low-cost micropower wireless system able to automatically detect oestrus period of cattle is presented. It was designed in cooperation with BQN, a company developing technology for the agribusiness industry in Uruguay. The tracker seizes the recent availability of 1 uA micropower accelerometers, LoRa long range transceivers, and FRAM microcontrollers, to achieve a coin cell battery powered paradigm for oestrus detection. The device records 3 axis acceleration information, process it, and periodically sends it to a server; it has a measured ultra low power consumption of 4 uA while collecting/processing data, reaching a very large (> 10km) communication distance using a star topology and LoRa technology at countryside areas. The scope of the project and this documentation is the entire hardware and firmware development, from the start idea, design and final implementation.Agencia Nacional de Investigación e Innovació

Performance evaluation of wake-up radio based wireless body area network

Abstract. The last decade has been really ambitious in new research and development techniques to reduce energy consumption especially in wireless sensor networks (WSNs). Sensor nodes are usually battery-powered and thus have very limited lifetime. Energy efficiency has been the most important aspect to discuss when talking about wireless body area network (WBAN) in particular, since it is the bottleneck of these networks. Medium access control (MAC) protocols hold the vital position to determine the energy efficiency of a WBAN, which is a key design issue for battery operated sensor nodes. The wake-up radio (WUR) based MAC and physical layer (PHY) have been evaluated in this research work in order to contribute to the energy efficient solutions development. WUR is an on-demand approach in which the node is woken up by the wake-up signal (WUS). A WUS switches a node from sleep mode to wake up mode to start signal transmission and reception. The WUS is transmitted or received by a secondary radio transceiver, which operates on very low power. The energy benefit of using WUR is compared with conventional duty-cycling approach. As the protocol defines the nodes in WUR based network do not waste energy on idle listening and are only awakened when there is a request for communication, therefore, energy consumption is extremely low. The performance of WUR based MAC protocol has been evaluated for both physical layer (PHY) and MAC for transmission of WUS and data. The probabilities of miss detection, false alarm and detection error rates are calculated for PHY and the probabilities of collision and successful data transmission for channel access method Aloha is evaluated. The results are obtained to compute and compare the total energy consumption of WUR based network with duty cycling. The results prove that the WUR based networks have significant potential to improve energy efficiency, in comparison to conventional duty cycling approach especially, in the case of low data-reporting rate applications. The duty cycle approach is better than WUR approach when sufficiently low duty cycle is combined with highly frequent communication between the network nodes

Secure OFDM System Design for Wireless Communications

Wireless communications is widely employed in modern society and plays an increasingly important role in people\u27s daily life. The broadcast nature of radio propagation, however, causes wireless communications particularly vulnerable to malicious attacks, and leads to critical challenges in securing the wireless transmission. Motivated by the insufficiency of traditional approaches to secure wireless communications, physical layer security that is emerging as a complement to the traditional upper-layer security mechanisms is investigated in this dissertation. Five novel techniques toward the physical layer security of wireless communications are proposed. The first two techniques focus on the security risk assessment in wireless networks to enable a situation-awareness based transmission protection. The third and fourth techniques utilize wireless medium characteristics to enhance the built-in security of wireless communication systems, so as to prevent passive eavesdropping. The last technique provides an embedded confidential signaling link for secure transmitter-receiver interaction in OFDM systems

DSP implementation of OFDM acoustic modem

The success of multicarrier modulation in the form of OFDM in radio channels illuminates a path one could take towards high-rate underwater acoustic communications,and recently there are intensive investigations on underwater OFDM. Processing power has increased to a point where orthogonal frequency division multiplexing (OFDM) has become feasible and economical. Since many wireless communication systems being developed use OFDM, it is a worthwhile research topic. Some examples of applications using OFDM include Digital subscriber line (DSL), Digital Audio Broadcasting (DAB),High definition television (HDTV) broadcasting, IEEE 802.11 (wireless networking standard).OFDM is a strong candidate and has been suggested or standardized in high speed communication systems. In this Thesis in first phase ,we analyzes the factor that affects the OFDM performance. The performance of OFDM was assessed by using computer simulations performed using Matlab7.2 .it was simulated under Additive white Gaussian noise (AWGN) ,Exponential Multipath channel and Carrier frequency offset conditions for different modulation schemes like binary phase shift keying (BPSK), Quadrature phase shift keying (QPSK),16 Quadrature amplitude modulation (16-QAM),64-Quadrature amplitude modulation(64-QAM)which are used for achieving high data rates.In second phase we implement the acoustic OFDM transmitter and receiver design of [4,5] on a TMS320C6713 DSP board. We analyze the workload and identify the most timeconsuming operations. Based on the workload analysis, we tune the algorithms and optimize the code to substantially reduce the synchronization time to 0.2 seconds and the processing time of one OFDM block to 2.7235 seconds on a DSP processor at 225 MHz. This experimentation provides guidelines on our future work to reduce the per-block processing time to be less than the block duration of 0.23 seconds for real time operations

Optimisation of vibration monitoring nodes in wireless sensor networks

This PhD research focuses on developing a wireless vibration condition monitoring (CM) node which allows an optimal implementation of advanced signal processing algorithms. Obviously, such a node should meet additional yet practical requirements including high robustness and low investments in achieving predictive maintenance. There are a number of wireless protocols which can be utilised to establish a wireless sensor network (WSN). Protocols like WiFi HaLow, Bluetooth low energy (BLE), ZigBee and Thread are more suitable for long-term non-critical CM battery powered nodes as they provide inherent merits like low cost, self-organising network, and low power consumption. WirelessHART and ISA100.11a provide more reliable and robust performance but their solutions are usually more expensive, thus they are more suitable for strict industrial control applications. Distributed computation can utilise the limited bandwidth of wireless network and battery life of sensor nodes more wisely. Hence it is becoming increasingly popular in wireless CM with the fast development of electronics and wireless technologies in recent years. Therefore, distributed computation is the primary focus of this research in order to develop an advanced sensor node for realising wireless networks which allow high-performance CM at minimal network traffic and economic cost. On this basis, a ZigBee-based vibration monitoring node is designed for the evaluation of embedding signal processing algorithms. A state-of-the-art Cortex-M4F processor is employed as the core processor on the wireless sensor node, which has been optimised for implementing complex signal processing algorithms at low power consumption. Meanwhile, an envelope analysis is focused on as the main intelligent technique embedded on the node due to the envelope analysis being the most effective and general method to characterise impulsive and modulating signatures. Such signatures can commonly be found on faulty signals generated by key machinery components, such as bearings, gears, turbines, and valves. Through a preliminary optimisation in implementing envelope analysis based on fast Fourier transform (FFT), an envelope spectrum of 2048 points is successfully achieved on a processor with a memory usage of 32 kB. Experimental results show that the simulated bearing faults can be clearly identified from the calculated envelope spectrum. Meanwhile, the data throughput requirement is reduced by more than 95% in comparison with the raw data transmission. To optimise the performance of the vibration monitoring node, three main techniques have been developed and validated: 1) A new data processing scheme is developed by combining three subsequent processing techniques: down-sampling, data frame overlapping and cascading. On this basis, a frequency resolution of 0.61 Hz in the envelope spectrum is achieved on the same processor. 2) The optimal band-pass filter for envelope analysis is selected by a scheme, in which the complicated fast kurtogram is implemented on the host computer for selecting optimal band-pass filter and real-time envelope analysis on the wireless sensor for extracting bearing fault features. Moreover, a frequency band of 16 kHz is analysed, which allows features to be extracted in a wide frequency band, covering a wide category of industrial applications. 3) Two new analysis methods: short-time RMS and spectral correlation algorithms are proposed for bearing fault diagnosis. They can significantly reduce the CPU usage, being over two times less and consequently much lower power consumptio

Multimodal Wearable Sensors for Human-Machine Interfaces

Certain areas of the body, such as the hands, eyes and organs of speech production, provide high-bandwidth information channels from the conscious mind to the outside world. The objective of this research was to develop an innovative wearable sensor device that records signals from these areas more conveniently than has previously been possible, so that they can be harnessed for communication. A novel bioelectrical and biomechanical sensing device, the wearable endogenous biosignal sensor (WEBS), was developed and tested in various communication and clinical measurement applications. One ground-breaking feature of the WEBS system is that it digitises biopotentials almost at the point of measurement. Its electrode connects directly to a high-resolution analog-to-digital converter. A second major advance is that, unlike previous active biopotential electrodes, the WEBS electrode connects to a shared data bus, allowing a large or small number of them to work together with relatively few physical interconnections. Another unique feature is its ability to switch dynamically between recording and signal source modes. An accelerometer within the device captures real-time information about its physical movement, not only facilitating the measurement of biomechanical signals of interest, but also allowing motion artefacts in the bioelectrical signal to be detected. Each of these innovative features has potentially far-reaching implications in biopotential measurement, both in clinical recording and in other applications. Weighing under 0.45 g and being remarkably low-cost, the WEBS is ideally suited for integration into disposable electrodes. Several such devices can be combined to form an inexpensive digital body sensor network, with shorter set-up time than conventional equipment, more flexible topology, and fewer physical interconnections. One phase of this study evaluated areas of the body as communication channels. The throat was selected for detailed study since it yields a range of voluntarily controllable signals, including laryngeal vibrations and gross movements associated with vocal tract articulation. A WEBS device recorded these signals and several novel methods of human-to-machine communication were demonstrated. To evaluate the performance of the WEBS system, recordings were validated against a high-end biopotential recording system for a number of biopotential signal types. To demonstrate an application for use by a clinician, the WEBS system was used to record 12‑lead electrocardiogram with augmented mechanical movement information

Real-Time Sensor Networks and Systems for the Industrial IoT

The Industrial Internet of Things (Industrial IoT—IIoT) has emerged as the core construct behind the various cyber-physical systems constituting a principal dimension of the fourth Industrial Revolution. While initially born as the concept behind specific industrial applications of generic IoT technologies, for the optimization of operational efficiency in automation and control, it quickly enabled the achievement of the total convergence of Operational (OT) and Information Technologies (IT). The IIoT has now surpassed the traditional borders of automation and control functions in the process and manufacturing industry, shifting towards a wider domain of functions and industries, embraced under the dominant global initiatives and architectural frameworks of Industry 4.0 (or Industrie 4.0) in Germany, Industrial Internet in the US, Society 5.0 in Japan, and Made-in-China 2025 in China. As real-time embedded systems are quickly achieving ubiquity in everyday life and in industrial environments, and many processes already depend on real-time cyber-physical systems and embedded sensors, the integration of IoT with cognitive computing and real-time data exchange is essential for real-time analytics and realization of digital twins in smart environments and services under the various frameworks’ provisions. In this context, real-time sensor networks and systems for the Industrial IoT encompass multiple technologies and raise significant design, optimization, integration and exploitation challenges. The ten articles in this Special Issue describe advances in real-time sensor networks and systems that are significant enablers of the Industrial IoT paradigm. In the relevant landscape, the domain of wireless networking technologies is centrally positioned, as expected