Survey on IOT in Waste Management System

Khan, Arshiya; Khachane, Ajitkumar

doi:10.1109/i-smac.2018.8653767

Cited by 11 publications

(8 citation statements)

References 7 publications

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“…As we focus on the uplink, the GW receives the useful signal, the interference coming from the other LoRa EDs, the aggregate interference coming from the underlying uncoordinated IoT networks, and the Additive White Gaussian Noise [25], [32]. Then, the baseband received signal by G j can be given by (2), where U j [n] denotes the useful signal, I j [n] the interference created by the other LoRa transmitters from the studied LoRa network, p(d ij ) the path loss attenuation, g t,i the i-th transmitter ED antenna gain, g r,j the j-th receiver antenna gain, h ij the fast fading coefficient between the ith transmitter and the j-th receiver, S i [n] the unit-variance signal sent by the i-th ED, ΦE k the set of all the interfering EDs that transmit data at the same time as the i-th ED, A[n] the Additive White Gaussian Noise (AWGN), Z j [n] the aggregate interference coming from the neighboring non-LoRa networks and N j [n] the total noise.…”

Section: Assumption 3 (Baseband Received Signal By a Gateway)mentioning

confidence: 99%

“…Thus, it is necessary to characterize both the interference and the noise implied in each LoRa communication, i.e. the powers of the elements I j [n] and N j [n] in (2). As shown previously and on Fig.…”

Section: B Signal-to-noise Ratio (Snr)mentioning

confidence: 99%

“…7 shows the Signal-to-Interference Ratio success probability vs. distance d = d i0 between the i-th ED and its relative 0-th GW. The curves are obtained thanks to (16), for λ E = 5 EDs per km 2 and λ G = 0.005, 0.01, 0.05 (orange curve, green curve and purple curves, respectively) GWs per km 2 .…”

Section: B Sir Analysismentioning

confidence: 99%

“…The importance of Internet of Things (IoT) in today's wireless communications systems is increasing day after day. Indeed, many applications related to these new types of Machine-to-Machine (M2M) communications are implemented and integrated in our everyday life: temperature monitoring at given locations in a city [1], waste management [2], smart city usages [3] such as public surveillance, intelligent traffic management [4], [5], smart building monitoring [6], [7], or intelligent healthcare control [8]. With the environmental and health issues that have emerged over the past few years, IoT is quickly becoming a cornerstone of our wellbeing.…”

Section: Introductionmentioning

confidence: 99%

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Stochastic Geometry-Based Analysis of the Impact of Underlying Uncorrelated IoT Networks on LoRa Coverage

et al. 2022

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IoT networks are more and more present nowadays. Some IoT protocols share the same bandwidth leading to interference on neighboring networks and decrease of overall coverage. To contribute to this problem, an analytical study of the coverage of a LoRa network with underlying uncoordinated IoT networks for uplink transmissions is presented in this paper. Using stochastic geometry, closed form analytical expressions are proposed allowing to analyze the success and coverage probabilities for a LoRa network. An appropriate model of the path loss including real-life values is used to characterize the log-distance propagation parameters. The interference comes from both the LoRa network itself and the underlying IoT networks, modeled with an α-stable distribution based on recent measurements. It is shown that for an environment with a huge amount of surrounding uncoordinated IoT networks, the gateways deployment should be doubled to reach a decent coverage probability, compared to an environment where the underlying interfering networks are not considered.

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Section: Assumption 3 (Baseband Received Signal By a Gateway)mentioning

confidence: 99%

Section: B Signal-to-noise Ratio (Snr)mentioning

confidence: 99%

Section: B Sir Analysismentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Stochastic Geometry-Based Analysis of the Impact of Underlying Uncorrelated IoT Networks on LoRa Coverage

et al. 2022

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“…Selanjutnya penelitian yang melibatkan integrasi antara IoT dengan machine learning di bidang lingkungan yaitu penelitian yang dilakukan oleh Khan dan Khachane [24]. Dalam penelitian ini, fokus pada menjaga kebersihan dari lingkungan.…”

Section: Gambar 8 Strukturunclassified

A Survey on Machine learning and IoT

Hardini

2019

ITEJ

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Internet of Things is an intelligence devices that can connect to any other devices. Based on that ability to connect and its intelligence, it makes people to create an intelligence device and capable to learn like human brain. To accomplish that goal, machine learning is the solution. Combination between machine learning and IoT generate a revolution in human life and application industry. The combination also generate new trend in market. Therefore, in this paper will be discuss about machine learning including machine learning technique and algorithm and also discuss about IoT including architecture and elements. Then in this paper will discuss about some researches that have already done that combine IoT with machine learning approach, including issue and challenge in those researches.

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