In this paper a low cost and user friendly remote controlled home automation system is presented using Arduino board, Bluetooth module, smartphone, ultrasonic sensor and moisture sensor. A smartphone application is used in the suggested system which allows the users to control up to 18 devices including home appliances and sensors using Bluetooth technology. Nowadays, most of conventional home automation systems are designed for special purposes while proposed system is a general purpose home automation system. Which can easily be implement in existing home. The suggested system has more features than conventional home automation systems such as an ultrasonic sensor is used for water level detection and soil moisture sensor is use for automatic plant irrigation system. This paper also describes the hardware and software architecture of system, future work and scope. The proposed prototype of home automation system is implemented and tested on hardware and it gave the exact and expected results.

Home automation system achieved great popularity in the last decades and it increases the comfort and quality of life. In this paper an overview of current and emerging home automation systems is discussed. Nowadays most home automation systems consist of a smartphone and microcontroller. A smart phone application is used to control and monitor the home appliances using different type of communication techniques. In this paper the working principle of different type of wireless communication techniques such as ZigBee, Wi-Fi, Bluetooth, EnOcean and GSM are studied and their features are compared with each other so the users can choose their own choice of technology to build home automation system. Moreover in this research work the survey of different home automation systems is discussed and their advantages and drawbacks are also highlighted.

Long Range-Frequency Hopping Spread Spectrum (LR-FHSS) has been recently introduced into the LoRaWAN protocol specification to increase network capacity and collision robustness, and enable direct connectivity between machine devices and the Low Earth Orbit (LEO) satellites. In this letter, we first construct the analytical and simulation models for packet delivery over LR-FHSS from ground nodes to a LEO satellite, and then use the developed analytic and simulation models to generate the numerical results. Our results reveal the potential feasibility of large-scale networks, demonstrate some trade-offs between the two new LR-FHSS-based data rates for the EU region, and reveal the key reasons for packet losses.

The offshore wind farms are gaining momentum due to their promise to offer sustainable energy with low pollution and greenhouse gas emission. However, despite all the immense technological progress of recent years, the operation in a harsh and hard-to-reach environment remains challenging. According to the reports, each offshore wind turbine requires five maintenance visits a year on average, and the cumulative repair costs constitute around 30% of the turbine’s life-cycle expenditure. Motivated by the advancement of massive machine-type connectivity (mMTC) and satellite technologies, in this study, we investigate the potential of these to enable remote monitoring of the offshore wind farms. Specifically, the two alternative architectures are considered. The indirect architecture relies on using a local mMTC gateway (GW) with a backbone over a reliable communication channel (e.g., satellite or wire-based). The direct approach implies the transmission of the data by sensors on the wind turbines directly to the mMTC GW on the low-Earth-orbit satellite. The details of the system design, the alternative implementation strategies, and relevant pros, cons, and tradeoffs are pin-pointed. Finally, we employ simulations using realistic deployment and traffic and advanced propagation and collision models to characterize these two approaches’ feasibility and packet delivery probability numerically when implemented over LoRaWAN mMTC technology.

The Long Range (LoRa) modulation enables low-cost and low-power communications, serving as the foundation for the widely adopted terrestrial low-power wide-area network (LPWAN) technology known as LoRaWAN. Owing to its effectiveness, this modulation scheme is emerging as a potential option to provide direct-to-satellite (DtS) connectivity supporting Internet-of-Things (IoT) applications in remote or hard-to-reach areas, and complementing existing terrestrial networks. Besides the link budget and interference, the Doppler effect is one of the main challenges in LoRa DtS connectivity. Earlier studies have extensively investigated the link budget and the network scalability aspects, confirming the feasibility of integrating LoRa with Low Earth Orbit (LEO) satellites. However, only a few studies examine the influence of the Doppler effect on LoRa DtS performance. Specifically, the majority of the available literature report empirical studies that analyze the Doppler effect solely for a specific set of communication parameters. There remains a need for extensive and comprehensive examination of LoRa DtS performance under a strong Doppler effect in the LEO scenario. In this paper, we discuss and thoroughly investigate the impact of the Doppler effect on the reliability of LoRa satellite links. In particular, we analytically study packet losses, distinguishing the effect of Doppler shift from Doppler rate, the latter being caused by the variation in the relative speed of LEO satellites with respect to a terrestrial IoT end-device. Our analysis accounts for the effects of key communications parameters and settings, such as bandwidths, carrier frequency, MAC payload, LEO satellite’s orbital height, and LoRaWAN low data rate optimization (LDRO). Notably, the results identify the LoRa boundaries for direct to LEO satellite connectivity and can facilitate the selection of suitable parameters for future system designs. Specifically, our results demonstrate that the packet delivery ratio of the most vulnerable spreading factor, i.e., SF12, exceeds 82% when using 125 kHz bandwidth, 433 MHz carrier frequency, and 59 bytes payload for a satellite orbiting at 560 km height.

Low-power wide-area networks (LPWANs) are emerging rapidly as a fundamental Internet of Things (IoT) technology because of their low-power consumption, long-range connectivity, and ability to support massive numbers of users. With its high growth rate, Long-Range (LoRa) is becoming the most adopted LPWAN technology. This research work contributes to the problem of LoRa spreading factor (SF) allocation by proposing an algorithm on the basis of K-means clustering. We assess the network performance considering the outage probabilities of a large-scale unconfirmed-mode class-A LoRa Wide Area Network (LoRaWAN) model, without retransmissions. The proposed algorithm allows for different user distribution over SFs, thus rendering SF allocation flexible. Such distribution translates into network parameters that are application dependent. Simulation results consider different network scenarios and realistic parameters to illustrate how the distance from the gateway and the number of nodes in each SF affects transmission reliability. Theoretical and simulation results show that our SF allocation approach improves the network’s average coverage probability up to 5 percentage points when compared to the baseline model. Moreover, our results show a fairer network operation where the performance difference between the best- and worst-case nodes is significantly reduced. This happens because our method seeks to equalize the usage of each SF. We show that the worst-case performance in one deployment scenario can be enhanced by $1.53$ times.