arXiv subjects

Abdallah Lakhdari

Publications and source records attributed to Abdallah Lakhdari.

35 records · Page 2Linked to original sources

arXiv2022

DIY-IPS: Towards an Off-the-Shelf Accurate Indoor Positioning System

We present DIY-IPS - Do It Yourself - Indoor Positioning System, an open-source real-time indoor positioning mobile application. DIY-IPS detects users' indoor position by employing dual-band RSSI fingerprinting of available WiFi access points. The app can be used, without additional infrastructural costs, to detect users' indoor positions in real time. We published our app as an open source to save other researchers time recreating it. The app enables researchers/users to (1) collect indoor positioning datasets with a ground truth label, (2) customize the app for higher accuracy or other research purposes (3) test the accuracy of modified methods by live testing with ground truth. We ran preliminary experiments to demonstrate the effectiveness of the app.

cs.NI↗

arXiv2022

IMAP: Individual huMAn mobility Patterns visualizing platform

Understanding human mobility is essential for the development of smart cities and social behavior research. Human mobility models may be used in numerous applications, including pandemic control, urban planning, and traffic management. The existing models' accuracy in predicting users' mobility patterns is less than 25%. The low accuracy may be justified by the flexible nature of the human movement. Indeed, humans are not rigid in their daily movement. In addition, the rigid mobility models may result in missing the hidden regularities in users' records. Thus, we propose a novel perspective to study and analyze human mobility patterns and capture their flexibility. Typically, the mobility patterns are represented by a sequence of locations. We propose to define the mobility patterns by abstracting these locations into a set of places. Labeling these locations will allow us to detect close-to-reality hidden patterns. We present IMAP, an Individual huMAn mobility Patterns visualizing platform. Our platform enables users to visualize a graph of the places they visited based on their history records. In addition, our platform displays the most frequent mobility patterns computed using a modified PrefixSpan approach.

cs.SI↗

arXiv2022

Maximizing Consumer Satisfaction of IoT Energy Services

We propose a novel Quality of Experience (QoE)-aware framework to crowdsource IoT energy services efficiently. The proposed framework leverages the provisioning of energy services as an auxiliary to increase consumers' satisfaction. A novel QoE model is developed as a metric to assess the consumers' satisfaction with the provisioning of energy services. Two novel composition algorithms, namely, Partial-Based (PB) and Demand-Based (DB) approaches, are proposed to ensure the highest QoE for consumers. Both approaches leverage the providers' flexibility and shareable nature of energy services to efficiently allocate services and optimize the QoE. A set of extensive experiments is conducted to evaluate the proposed approaches' efficiency and effectiveness.

cs.DC↗

arXiv2022

You Are What You Use: Usage-based Profiling in IoT Environments

Habit extraction is essential to automate services and provide appliance usage insights in the smart home environment. However, habit extraction comes with plenty of challenges in viewing typical start and end times for particular activities. This paper introduces a novel way of identifying habits using an ensemble of unsupervised clustering techniques. We use different clustering algorithms to extract habits based on how static or dynamic they are. Silhouette coefficients and a novel noise metric are utilized to extract habits appropriately. Furthermore, we associate the extracted habits with time intervals and a confidence score to denote how confident we are that a habit is likely to occur at that time.

cs.HC↗

arXiv2022

Autonomous Delivery of Multiple Packages Using Single Drone in Urban Airspace

Current drone delivery solutions mainly focus on single package delivery using one drone. However, the recent developments in drone technology enable a drone to deliver multiple packages in a single trip. We use the nearest destination first strategy for the faster delivery of packages in a skyway network. This demonstration is a proof-of-concept prototype for the multi-package delivery in urban airspace following a skyway network. We deploy and test this multi-package drone delivery in an indoor testbed environment using a 3D model of Sydney CBD. Demo: https://youtu.be/YTwsIfUvWPc

cs.RO↗

arXiv2022

The Nudging Effect on Tracking Activity

Wearables activity trackers are becoming widely adopted to understand individual behavior. Understanding behavior may help in self-regulation such as self-monitoring, goal-setting, self-corrective, etc.; Nevertheless, challenges exist in attaining consistent use and adoption of wearables, which hinders behavior understanding. Research has suggested that nudging strategies may change and sustain human engagement. However, it is still unknown how nudging may affect human wearing behavior on an individual level. We conducted a six-month study in which we tested several nudging techniques on the same participants. The preliminary results of our research show that participants perform better when a nudging strategy is applied. In addition, participants responded differently to different nudging techniques. Future research can focus on developing an individual-based nudging mechanism to encourage users to wear their devices consistently.

cs.HC↗

arXiv2022

Quality of Experience Optimization in IoT Energy Services

We propose a novel Quality of Experience (QoE) metric as a key criterion to optimize the composition of energy services in a crowdsourced IoT environment. A novel importance-based composition algorithm is proposed to ensure the highest QoE for consumers. A set of experiments is conducted to evaluate the proposed approaches' effectiveness and efficiency.

cs.DC↗

arXiv2022

Density-Based Pruning of Drone Swarm Services

We propose a novel framework for the recommendation of swarm-based drone delivery services based on the consumers preferences. We propose a density-based pruning approach that uses the concept of partnerships with charging station providers to reduce the search space of swarm-based drone service delivery providers. A weighted service composition algorithm is proposed that considers the providers capabilities and consumers' preferences in selecting the best next service. We propose a voting-based recommendation algorithm to select the best providers. We conduct a set of experiments to evaluate the efficiency of the framework in terms of consumer satisfaction, run-time, and search space reduction cost.

cs.RO↗

arXiv2022

Wireless IoT Energy Sharing Platform

Wireless energy sharing is a novel convenient alternative to charge IoT devices. In this demo paper, we present a peer-to-peer wireless energy sharing platform. The platform enables users to exchange energy wirelessly with nearby IoT devices. The energy sharing platform allows IoT users to send and receive energy wirelessly. The platform consists of (i) a mobile application that monitors and synchronizes the energy transfer among two IoT devices and (ii) and a backend to register energy providers and consumers and store their energy transfer transactions. The eveloped framework allows the collection of a real wireless energy sharing dataset. A set of preliminary experiments has been conducted on the collected dataset to analyze and demonstrate the behavior of the current wireless energy sharing technology.

cs.DC↗

arXiv2021

Composing Energy Services in a Crowdsourced IoT Environment

We propose a novel framework for composing crowdsourced wireless energy services to satisfy users' energy requirements in a crowdsourced Internet of Things (IoT) environment. A new energy service model is designed to transform the harvested energy from IoT devices into crowdsourced services. We propose a new energy service composability model that considers the spatio-temporal aspects and the usage patterns of the IoT devices. A multiple local knapsack-based approach is developed to select an optimal set of partial energy services based on the deliverable energy capacity of IoT devices. We propose a heuristic-based composition approach using the temporal and energy capacity distributions of services. Experimental results demonstrate the effectiveness and efficiency of the proposed approach.

cs.DC↗

arXiv2021

Fairness-aware Crowdsourcing of IoT Energy Services

We propose a Novel Fairness-Aware framework for Crowdsourcing Energy Services (FACES) to efficiently provision crowdsourced IoT energy services. Typically, efficient resource provisioning might incur an unfair resource sharing for some requests. FACES, however, maximizes the utilization of the available energy services by maximizing fairness across all requests. We conduct a set of preliminary experiments to assess the effectiveness of the proposed framework against traditional fairness-aware resource allocation algorithms. Results demonstrate that the IoT energy utilization of FACES is better than FCFS and similar to Max-min fair scheduling. Experiments also show that better fairness is achieved among the provisioned requests using FACES compared toFCFS and Max-min fair scheduling.

cs.DC↗

arXiv2021

Occupancy Estimation from Thermal Images

We propose a non-intrusive, and privacy-preserving occupancy estimation system for smart environments. The proposed scheme uses thermal images to detect the number of people in a given area. The occupancy estimation model is designed using the concepts of intensity-based and motion-based human segmentation. The notion of difference catcher, connected component labeling, noise filter, and memory propagation are utilized to estimate the occupancy number. We use a real dataset to demonstrate the effectiveness of the proposed system.

cs.CV↗

arXiv2021

Proactive Composition of Mobile IoT Energy Services

We propose a novel proactive composition framework of wireless energy services in a crowdsourced IoT environment. We define a new model for energy services and requests that includes providers' and consumers' mobility patterns and energy usage behavior. The proposed composition approach leverages the mobility and energy usage behavior to generate energy services and requests proactively. Preliminary experimental results demonstrate the effectiveness of generating proactive energy requests and composing proactive services.

cs.DC↗

arXiv2021

Combating fake news by empowering fact-checked news spread via topology-based interventions

Rapid information diffusion and large-scaled information cascades can enable the undesired spread of false information. A small-scaled false information outbreak may potentially lead to an infodemic. We propose a novel information diffusion and intervention technique to combat the spread of false news. As false information is often spreading faster in a social network, the proposed diffusion methodology inhibits the spread of false news by proactively diffusing the fact-checked information. Our methodology mainly relies on defining the potential super-spreaders in a social network based on their centrality metrics. We run an extensive set of experiments on different networks to investigate the impact of centrality metrics on the performance of the proposed diffusion and intervention models. The obtained results demonstrate that empowering the diffusion of fact-checked news combats the spread of false news further and deeper in social networks.

cs.SI↗

arXiv2020

Crowdsharing Wireless Energy Services

We propose a novel self-sustained ecosystem for energy sharing in the IoT environment. We leverage energy harvesting, wireless power transfer, and crowdsourcing that facilitate the development of an energy crowdsharing framework to charge IoT devices. The ubiquity of IoT devices, coupled with the potential ability for sharing energy, provides new and exciting opportunities to crowdsource wireless energy, thus enabling a green alternative for powering IoT devices anytime and anywhere. We discuss the crowdsharing of energy services, open challenges, and proposed solutions.

cs.DC↗

arXiv2020

Elastic Composition of Crowdsourced IoT Energy Services

We propose a novel type of service composition, called elastic composition which provides a reliable framework in a highly fluctuating IoT energy provisioning settings. We rely on crowdsourcing IoT energy (e.g., wearables) to provide wireless energy to nearby devices. We introduce the concepts of soft deadline and hard deadline as key criteria to cater for an elastic composition framework. We conduct a set of experiments on real-world datasets to assess the efficiency of the proposed approach.

cs.DC↗

arXiv2020

Fluid Composition of Intermittent IoT Energy Services

We propose a novel fluid composition approach of wireless energy services in a crowdsourced IoT environment. The proposed approach selects an optimal set of dynamic energy services according to the consumer's requirements. We leverage the mobility patterns of the crowd in confined areas to capture the intermittent behavior of IoT energy services. We model the IoT energy services based on their mobility patterns to propose a knapsack-based heuristic for the fluid composition. Experimental results demonstrate the efficiency of the proposed approach.

cs.DC↗