The rapid growth of Internet-of-Things (IoT) in the current decade has led to the development of a multitude of new access technologies targeted at low-power, wide area networks (LP-WANs). However, this has also created another challenge pertaining to technology selection. This paper reviews the performance of LP-WAN technologies for IoT, including design choices and their implications. We consider Sigfox, LoRaWAN, WavIoT, random phase multiple access (RPMA), narrowband IoT (NB-IoT), as well as LTE-M and assess their performance in terms of signal propagation, coverage and energy conservation. The comparative analyses presented in this paper are based on available data sheets and simulation results. A sensitivity analysis is also conducted to evaluate network performance in response to variations in system design parameters. Results show that each of RPMA, NB-IoT, and LTE-M incurs at least 9 dB additional path loss relative to Sigfox and LoRaWAN. This paper further reveals that with a 10% improvement in receiver sensitivity, NB-IoT 882 MHz and LoRaWAN can increase coverage by up to 398% and 142%, respectively, without adverse effects on the energy requirements. Finally, extreme weather conditions can significantly reduce the active network life of LP-WANs. In particular, the results indicate that operating an IoT device in a temperature of −20 °C can shorten its life by about half; 53% (WavIoT, LoRaWAN, Sigfox, NB-IoT, and RPMA) and 48% in LTE-M compared with environmental temperature of 40 °C.

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Low-Power Wide Area Network Technologies for Internet-of-Things: A Comparative Review

In a few years, the world will be populated by billions of connected devices that will be placed in our homes, cities, vehicles, and industries. Devices with limited resources will interact with the surrounding environment and users. Many of these devices will be based on machine learning models to decode meaning and behavior behind sensors’ data, to implement accurate predictions and make decisions. The bottleneck will be the high level of connected things that could congest the network. Hence, the need to incorporate intelligence on end devices using machine learning algorithms. Deploying machine learning on such edge devices improves the network congestion by allowing computations to be performed close to the data sources. The aim of this work is to provide a review of the main techniques that guarantee the execution of machine learning models on hardware with low performances in the Internet of Things paradigm, paving the way to the Internet of Conscious Things. In this work, a detailed review on models, architecture, and requirements on solutions that implement edge machine learning on Internet of Things devices is presented, with the main goal to define the state of the art and envisioning development requirements. Furthermore, an example of edge machine learning implementation on a microcontroller will be provided, commonly regarded as the machine learning “Hello World”.

https://www.mdpi.com/1424-8220/20/9/2533/pdf

Edge Machine Learning for AI-Enabled IoT Devices: A Review

Wireless sensor networks (WSNs) provide noteworthy benefits over traditional approaches for several applications, including smart homes, healthcare, environmental monitoring, and homeland security. WSNs are integrated with the Internet Protocol (IP) to develop the Internet of Things (IoT) for connecting everyday life objects to the internet. Hence, major challenges of WSNs include: (i) how to efficiently utilize small size and low-power nodes to implement security during data transmission among several sensor nodes; (ii) how to resolve security issues associated with the harsh and complex environmental conditions during data transmission over a long coverage range. In this study, a secure IoT-based smart home automation system was developed. To facilitate energy-efficient data encryption, a method namely Triangle Based Security Algorithm (TBSA) based on efficient key generation mechanism was proposed. The proposed TBSA in integration of the low power Wi-Fi were included in WSNs with the Internet to develop a novel IoT-based smart home which could provide secure data transmission among several associated sensor nodes in the network over a long converge range. The developed IoT based system has outstanding performance by fulfilling all the necessary security requirements. The experimental results showed that the proposed TBSA algorithm consumed less energy in comparison with some existing methods.

A Novel Secure IoT-Based Smart Home Automation System Using a Wireless Sensor Network.

In this review paper, we have discussed the existing state-of-the-art practices of improved intelligent features, controlling parameters and Internet of things (IoT) infrastructure required for smart building. The main focus is on sensing, controlling the IoT infrastructure which enables the cloud clients to use a virtual sensing infrastructure using communication protocols. The following are some of the intelligent features that usually make building smart such as privacy and security, network architecture, health services, sensors for sensing, safety, and overall management in smart buildings. As we know, the Internet of Things (IoT) describes the ability to connect and control the appliances through the network in smart buildings. The development of sensing technology, control techniques, and IoT infrastructure give rise to a smart building more efficient. Therefore, the new and problematic innovation of smart buildings in the context of IoT is to a great extent and scattered. The conducted review organized in a scientific manner for future research direction which presents the existing challenges, and drawbacks.

Sensing, Controlling, and IoT Infrastructure in Smart Building: A Review

A course on the emerging topic “Smart Sensors and Internet of Things (IoT)” has been designed, developed, and delivered from 21st March 2016 to 31st March 2016 in the Department of Electrical Engineering, Jamia Millia Islamia (Central University), New Delhi-110025, India. This course was organized under a program initiated by the Government of India, entitled “Global Initiative of Academic Networks” for higher education. The basic objective is to bring the internationally and nationally acclaimed scientists on a single platform to motivate young minds of India so that India’s scientific and technological capacity reach global excellence. The course was designed to develop the technical skills for the students, the researchers, the engineers, and the faculties, who desire to address some of the issues faced by the people around the world in the fields of smart sensors and IoTs with applications in smart homes, smart cities, smart grids, smart environment, smart transport, and so on. The assessment of the course by the participants shows extreme usefulness of it.

Smart Sensors and Internet of Things: A Postgraduate Paper

An Internet of Things (IoT) enabled intelligent sensor node has been designed and developed for smart city applications. The fabricated sensor nodes count the number of pedestrians, their direction of travel along with some ambient parameters. The Field of View (FoV) of Fresnel lens of commercially available passive infrared (PIR) sensors has been specially tuned to monitor the movements of only humans and no other domestic animals such as dogs, cats etc. The ambient parameters include temperature, humidity, pressure, Carbon di Oxide (CO2) and total volatile organic component (TVOC). The monitored data are uploaded to the Internet server through the Long Range Wide Area Network (LoRaWAN) communication system. An intelligent algorithm has been developed to achieve an accuracy of 95% for the pedestrian count. There are a total of 74 sensor nodes that have been installed around Macquarie University and continued working for the last six months.

https://www.mdpi.com/1424-8220/19/15/3374/pdf

IoT enabled intelligent sensor node for smart city: pedestrian counting and ambient monitoring

This review paper explains the available long-range wireless technologies for IoT applications. There are licensed and unlicensed spectrums available with a few advantages and disadvantages. The licensed spectrum has strong signal levels, low noise level, better throughput and better range performances. Initial costing of licensed spectrum is hard, and it is expensive to acquire. The unlicensed spectrum is free to obtain and does not cause harmful interference. All the technologies are discussed which will be useful to decide to develop any applications.

Long-range wireless technologies for IoT applications: A review

The need to develop a low-power, low-cost nitrate, phosphate, and pH sensor and sensing system is essential for monitoring water quality in real-time. A novel interdigital sensor has been fabricated and characterized for temperature, nitrate, phosphate, and pH detection in water. The sensor is fabricated using the 3D printing technique where electrodes are formed using Multi-Walled Carbon Nanotubes (MWCNTs), and the substrate is developed using Polydimethylsiloxane (PDMS). The sensor is characterized by Electrochemical Impedance Spectroscopy (EIS) to determine various temperatures, pH levels, nitrate, and phosphate concentrations. Experimental outcomes prove that the developed sensor can distinguish nitrate and phosphate concentrations ranging from 0.1 ppm 30 ppm, pH values from 1.71 12.59, temperature from 0 45circ C. The sensitivity for temperature, nitrate, phosphate, and pH level of the sensor are 1.1974Ω/circ C, 1.9396Ω/ppm, 0.8839Ω/ppm and 1.0295Ω, respectively. A location-independent portable smart sensing system with LoRa connectivity is also developed to surveil water quality and get feedback from the experts. A machine learning algorithm trains the Arduino-based system and determines temperature, nitrate and phosphate concentrations, and pH level in real water samples. All the outcomes are compared with the standard method for validation. The sensor and the sensing system’s performances are highly stable, reliable, and repeatable to be a part of a smart sensing network for continuous water quality monitoring.

An IoT-enabled Portable Water Quality Monitoring System with MWCNT/PDMS Multifunctional Sensor for Agricultural Applications

The use of multi-walled carbon nanotube (MWCNT)-based sensors for strain-strain applications is showcased in this paper. Extensive use of MWCNTs has been done for the fabrication and implementation of flexible sensors due to their enhanced electrical, mechanical, and thermal properties. These nanotubes have been deployed both in pure and composite forms for obtaining highly efficient sensors in terms of sensitivity, robustness, and longevity. Among the wide range of applications that MWCNTs have been exploited for, strain-sensing has been one of the most popular ones due to the high mechanical flexibility of these carbon allotropes. The MWCNT-based sensors have been able to deduce a broad spectrum of macro- and micro-scaled tensions through structural changes. This paper highlights some of the well-approved conjugations of MWCNTs with different kinds of polymers and other conductive nanomaterials to form the electrodes of the strain sensors. It also underlines some of the measures that can be taken in the future to improve the quality of these MWCNT-based sensors for strain-related applications.

Multi-Walled Carbon Nanotubes-Based Sensors for Strain Sensing Applications.

Pervasive sensing facilitated by Wireless Sensor Networks (WSNs) technologies offers the integration of modern technology into daily routine. The smart sensing approach offers the ability to sense ambient parameters and the use of different objects in the urban environment. Identification and monitoring technologies, WSNs, wireless communication protocols and dispersed intelligence for objects are primitive elements of a smart environmental solution. The WSNs with the application of the Internet of Things (IoT) and Cloud computing are producing smart home solutions. The present research work aims to develop smart home and building solutions based on IoT and cloud computing. The research work recorded recent practical challenges and limitations encountered while designing the IoT-based smart environment. The research identifies the IoT idea, through the conjunction of WSNs, the Internet and distributed computing with data mining and machine learning, as an approach to apply in smart homes to benefit humankind.

Eshrat E. Alahi

Papers

IoT enabled intelligent sensor node for smart city: pedestrian counting and ambient monitoring

Long-range wireless technologies for IoT applications: A review

An IoT-enabled Portable Water Quality Monitoring System with MWCNT/PDMS Multifunctional Sensor for Agricultural Applications

Multi-Walled Carbon Nanotubes-Based Sensors for Strain Sensing Applications.

Internet of Things for smart homes and buildings