Design and implementation of a robust data logging and satellite telemetry system for remote cryospheric research

In recent years, the Internet of Things (IoT) technology has shown a good momentum of development and has been widely used in various fields of society. Satellite IoT, as an important complement and extension of the ground IoT, provides services in areas where oceanic and desert areas cannot build terrestrial IoT base stations. However, due to limited spectrum resources, spectrum sharing between terrestrial IoT and satellite IoT is likely to be required, which will inevitably lead to uplink and downlink co-channel interference between systems. This paper analyzes various interference scenarios that may occur on the uplink and downlink of terrestrial IoT and satellite IoT. Then, we establishes a global dynamic model of interference volume, and obtains the dynamic distribution of global interference of low-orbit satellite IoT through simulation. Finally, the paper uses the low-orbit satellite IoT global interference scenarios, interference distribution model and interference analysis model to obtain the dynamic analysis of the global uplink and downlink interference of the low-orbit satellite IoT, and uses the interference analysis results to give suggestions for the deployment of Low-orbit Satellite IoT.

Machine type connectivity (MTC) is the key enabler for versatile Internet of Things (IoT) applications, which are becoming an essential component of everyday life. However, the availability of connectivity in general and MTC in particular around the globe is still not uniform. Motivated by this fact, in this paper, we focus on the technology which has the potential to support unprecedented coverage - the satellite IoT (SIoT). In the paper, we pinpoint the key drivers of satellite IoT development. Then we discuss, analyze and classify the IoT use cases and prominent applications for SIoT, and provide some insight into the current status of SIoT. Next, we discuss the key performance indicators (KPIs) for SIoT and map them against the key-value indicators (KVIs) and sustainable development goals (SDGs) formulated by the UN. Finally, we pinpoint the challenges and potential directions for further SIoT studies.

The Center for Product Design and Manufacturing (CPDM) of University Malaya going to take part in the World Solar Challenge (WSC) 2009. It is a biannual solar powered car race over 3021 km from Darwin to Adelaide. The aim of this project is to build a system for monitoring performance of the solar vehicle during testing and race, a data acquisition and telemetry (DaqT) system is needed. In this project, a DaqT system will be developed using National Instruments’ (NI) LabVIEW, compactRIO (cRIO) and MaxStream Xstream Radio Frequency modules. The DaqT is able to measure signals from sensors which are thermocouples, current transducers, battery storage and tachometer. Experiment is conducted to investigate the capability of the DaqT system to process signals from essential sensors, transmit data with wireless communication and data logging. The results of this project from the experiment, the DaqT manage to transmit data in open space up to 700 meters and the percentages of the error is below 5%.

The explosive growth of Internet of Things (IoT) terminals poses dual challenges for wide-area access and system overhead. Satellite networks provide global coverage but face stringent transmit power constraints due to limited onboard energy and long-distance propagation. Low-resolution Analog-to-Digital Converters (ADCs) can reduce terminal complexity, yet their coarse quantization introduces nonlinear distortion that conventional power allocation cannot effectively handle. This letter develops an analytical model and proposes a quantization distortion-aware power allocation algorithm for OFDM-based satellite IoT downlink using low-resolution ADCs. Leveraging Bussgang decomposition and Price theorem, we model quantization distortion and derive an upper bound on the ergodic achievable rate. Based on this bound, we propose a power allocation algorithm combining the Lagrangian multiplier method and gradient projection, subject to total transmit power and spectral constraints. Simulation results confirm that the proposed algorithm achieves near-optimal ergodic achievable rate with more stringent constraints compared to general optimization method. This work provides a resource-efficient framework for large-scale satellite IoT connectivity.

This paper examines potential performances of the Spread Spectrum-based random access technique and proposes an Improved Spread Spectrum Aloha (ISSA) protocol for the return channel in satellite Internet of Things (IoT) based on the beam-hopping technique. The key design driver and detailed solution of ISSA protocol are presented in this work and it is shown that the proposed protocol achieves high throughput and low collision probability. To match user/traffic distribution, delay requirement and channel condition with beam allocation better, a low-complexity heuristic beam scheduling algorithm and a more effective Maximum-Weighted Clique (MWC) algorithm have been proposed. The heuristic algorithm considers the user/traffic distribution, inter-beam interference, and fairness primarily. However, the MWC algorithm gives considerations not only on above factors, but also on delay requirement and channel condition (path loss and rain attenuation) to maximize system capacity. The beam angle and interference avoidance threshold are proposed to measure the inter-beam interference, and the link propagation loss and rain attenuation are considered meanwhile in the channel condition. In the MWC algorithm, we construct an auxiliary graph to find the maximum-weighted clique and derive the weighting approach to be applied in different application scenarios. The performance evaluation of our ISSA protocol compared with the SSA protocol is presented, which achieves a gain of . The simulation of the ISSA protocol combined with round robin, heuristic, and MWC beam scheduling for the return link in beam-hopping satellite IoTs is also provided. The results indicate that the throughput in nonuniform user distribution is much lower than in the uniform case without the beam scheduling algorithm. Through the application of the scheduling algorithm, the throughput performance can approach the uniform distribution. Finally, the degree of user satisfaction with different scheduling approaches is presented, which validates the effectiveness of heuristic and MWC algorithms.

The development process of complex technical products of the last years shows an increasing amount of sensors, electronic control units, data logging and monitoring systems within consumer goods (e.g. automobiles, washing machines) and industrial goods (e.g. machine tools, manufacturing sys-tems). In many cases, the main goal of data logging is monitoring, controlling and optimisation of the product functionalities within the usage phase. A further aim is the fulfilment of the process capability of manufacturing processes. Therefore, the layout of the concept of operating data logging and monitoring systems—especially operating data (mainly type, volume, and format) as well as hardware (like sensors and storage)-is designed by the development engineer within the product concept development phase. This paper discusses challenges, requirements and approaches for future conceptual design of operating data logging concepts of technical products related to reliability engineering. Base of operations is the state of art. Based on that, the concept for operating data logging within a monitoring system is shown. The concept draft is subdivided in three parts which are divided as follows: part one deals with data analytics, part two contains data requirements, and part three focuses on hardware requirements. The presented research study was worked out on the international research platform “Computational Reliability Engineering in Product Development and Manufacturing (CRE) – 2017” and contains contributions of universities, institutes and original equipment manufacturers of industrial nations: Germany, United Kingdom, Japan, Turkey and France.

construction process of a NATM tunnel consists of geological data logging and rock mass classification, monitoring of the changes of rock strain and stress, as well as blasting and excavation. Nevertheless, the disadvantages of traditional manual recording of tunnel-related information are: 1) it is difficult to record data in the poor jobsite environment, 2) the storage of these data is very poor, 3) it is not easy to analyze these data to provide more in-depth information to the construction process. This paper adopts decision support system (DSS) to establish The Integrated Rock Tunnel Data Logging and Decision-aid System (RTLD). system consists of database subsystem, decision module subsystem and dialog subsystem. system has a convenient decision-aid interface and an integrated data structure that encompasses all the tunnel-related information. functions of the system include geological data logs (through semi-automatic image processing), 3D geology prediction, rock mass classification, rock monitoring data recording and graphical display, data recording and display of construction process and resources, and data correlation analysis.

LoRa has been widely used in the Internet of Things (IoT). However, since LoRa only supports single symbol transmission in its bandwidth, the bit rate of LoRa is limited. This restricts the future development of LoRa, such as Smart Home, Internet of Vehicles, Satellite IoT, etc. Toward this end, based on the energy convergence characteristic of LoRa symbol in the fractional domain, we propose a multiplexed LoRa (MuLoRa) which transmits multiple LoRa symbols simultaneously in the same bandwidth. By adding address bits, the collision between multiple LoRa symbols of MuLoRa is avoided. Considering the hardware consumption of MuLoRa modulation in the time domain, a fractional domain MuLoRa modulation method based on fractional Fourier transform (FRFT) is designed. Simulation results show that MuLoRa can significantly improve the transmission bit rate than conventional LoRa under the same bandwidth. And MuLoRa can be configured more flexibly to meet the performance requirements of rate, power, collision avoidance and BER in different application scenarios in the future high data rate IoT era.

An integrated foot transducer and data logging system for dynamic assessment of lower limb exerted forces during agricultural machinery operations

Internet of Things (IoT) and direct-access Satellite IoT (SIoT) systems demand short block-length communication to accommodate brief transmissions under strict power constraints. In this context, it is critical to ensure high error correction reliability with minimal energy. One prominent candidate for Forward Error Correction (FEC) is Polar codes. Introduced by Arikan in 2009, Polar codes achieve the capacity of binary-input discrete memoryless channels through the phenomenon of channel polarization. While generalizing Polar codes to non-binary fields <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\mathbb{GF}(q)$</tex> can yield improved performance compared to their binary counterpart at long block lengths, they fall short at short block length even when applying techniques such as frozen-bit-pattern and kernel optimization. In this paper, additional strategies are evaluated that go beyond these baseline techniques. In detail, kernel optimization is extended towards a multi-kernel approach and a joint optimization of modulation order and code rate on system level is proposed. Simulation results demonstrate that under these careful optimizations, non-binary Polar codes can indeed outperform binary Polar codes for short block length, as well, making them the optimal channel-coding choice for SIoT applications.

In recent years, separating locators and identifiers has been widely applied in satellite Internet of things (IoT) networks. The identifier is the terminal identity, and the locator is used as the identification of routing. Therefore, an enormous mapping server is applied to store the mapping information between the identifier and locator, which needs to be updated timely and effectively. In this paper, a hybrid mapping server is developed to store the mapping table items, applied in the Global and Local aggregation nodes. Local aggregation nodes could cache the mapping table items locally and accelerate the mapping query by completing the query locally. In general, due to the limited storage space of Local aggregation nodes, only a proportion of the mapping information obtained from Global aggregation nodes could be stored, making the selection of cached mapping table items essential. In our work, a prefetch and cache replacement method (PCRA) based on Thompson sampling is proposed to select the appropriate mapping table items to cache, which combines the characteristics of the large number of satellite IoT terminals and fast terminal moving speed. It is shown that, compared with the traditional cache strategies, PCRA could improve the cache hit rate by around 10%.

Due to the scarcity of spectrum resources in Non-orthogonal Multiple Access (NOMA) systems and insufficient satellite-ground integration in satellite Internet of Things (IoT), this paper investigates its issue in spectrum resource management. We propose a resource allocation method based on Multi-Agent Deep Deterministic Policy Gradient (MADDPG) for NOMA enabled satellite IoT. We formulate the spectrum allocation problem of the satellite-ground integrated network as a distributed optimization problem. Then we decouple the problem into two sub-problems. Firstly, a user grouping method based on matching coefficients is defined, and a Linear Programming (LP) method is utilized for obtaining solution. Secondly, the power allocation problem is transformed into a multi-agent problem, where MADDPG is employed to allocate the power. Through this approach, the system is capable of real-time user association and spectrum resource allocation optimization, achieving optimal user grouping while maximizing system transmission rate. Based on the simulation results, the MADDPG-based method demonstrates fast convergence within 100 training iterations. The proposed MADDPG-based resource management method also achieves increased system transmission rate with more effective matching outcomes over Deep Deterministic Policy Gradient (DDPG), Orthogonal Multiple Access (OMA), and random allocation baselines.

A low-complexity minimum mean square error (MMSE) equalizer with hybrid interference cancellation (HIC) for non-orthogonal multiple access (NOMA) based Low Earth Orbit (LEO) satellite Internet of Things (IoT) systems is presented in this paper. First, a HIC grouping strategy is proposed with the signal-to-interference-plus-noise ratio (SINR) threshold, which can effectively reduce the number of iteration and decoding times. Besides, a reduced-complexity MMSE equalizer based on the matrix expansion and Greville criterion is adopted to avoid the direct computation of matrix inversion. The results show that our proposed scheme can significantly reduce the overhead and processing delay while preserving a good performance.

A web-based CO2 measurement device and a data network system in Indonesia which consist of the CO2 measurement device, the local data processor system, and the central data processor system has been built. The CO2 measurement device consist of the GMM220 CO2 sensor module from Vaisala and the data logger system. The data logger output consists of location, time, date, CO2 concentration, and input voltage, which packed all up in one data form with RGPGHG as the data header. The data logger system store the data into SD Card memory and ends it to the local data processor system. The CO2 Monitor Software in the local data processor system processes the data and display the graphical data which shows the maximum, minimum and average values of the data, and also sends the data to the central data processor system. The central data processor system displays data from several local data processor systems in the form of real time web-based graphical data and text, so the internet users can access and download its data. The development result device has been applicated in Kototabang, and the CO2 measurement device has been connected as well to the central data processor system in Bandung via the internet network to perform the web-based CO2 data network system in Indonesia. According to the data stored by the central data processor system for the periode of 1 - 26 March 2010, it shows that the CO2 concentration in Kototabang have an average of 403,5 ppm, with the maximum of 476,9 ppm and the minimum of 364,7 ppm. While the CO2 concentration in Bandung have an average of 397,2 ppm, with the maximum of 502,5 ppm and the minimum of 325,3 ppm. Key words: Data logger, CO2 sensor, Web-based interface

Nowadays, the Internet of Things (IoT) has become widely used at various places and for various applications. To facilitate this trend, we have developed the IoT application server platform called SEMAR (Smart Environmental Monitoring and Analytical in Real-Time), which offers standard features for collecting, displaying, and analyzing sensor data. An edge device is usually installed to connect sensors with the server, where the interface configuration, the data processing, the communication protocol, and the transmission interval need to be defined by the user. In this paper, we proposed an edge device framework for SEMAR to remotely optimize the edge device utilization with three phases. In the initialization phase, it automatically downloads the configuration file to the device through HTTP communications. In the service phase, it converts data from various sensors into the standard data format and sends it to the server periodically. In the update phase, it remotely updates the configuration through MQTT communications. For evaluations, we applied the proposal to the fingerprint-based indoor localization system (FILS15.4) and the data logging system. The results confirm the effectiveness in utilizing SEMAR to develop IoT application systems.