Showing papers on "Smart device published in 2019"

Who's In Control?: Interactions In Multi-User Smart Homes

Abstract: Adoption of commercial smart home devices is rapidly increasing, allowing in-situ research in people's homes. As these technologies are deployed in shared spaces, we seek to understand interactions among multiple people and devices in a smart home. We conducted a mixed-methods study with 18 participants (primarily people who drive smart device adoption in their homes) living in multi-user smart homes, combining semi-structured interviews and experience sampling. Our findings surface tensions and cooperation among users in several phases of smart device use: device selection and installation, ordinary use, when the smart home does not work as expected, and over longer term use. We observe an outsized role of the person who installs devices in terms of selecting, controlling, and fixing them; negotiations between parents and children; and minimally voiced privacy concerns among co-occupants, possibly due to participant sampling. We make design recommendations for supporting long-term smart homes and non-expert household members.

Sensors of Smart Devices in the Internet of Everything (IoE) Era: Big Opportunities and Massive Doubts

Abstract: Smart device industry allows developers and designers to embed different sensors, processors, and memories in small-size electronic devices. Sensors are added to enhance the usability of these devices and improve the quality of experience through data collection and analysis. However, with the era of big data and machine learning, sensors’ data may be processed by different techniques to infer various hidden information. The extracted information may be beneficial to device users, developers, and designers to enhance the management, operation, and development of these devices. However, the extracted information may be used to compromise the security and the privacy of humans in the era of Internet of Everything (IoE). In this work, we attempt to review the process of inferring meaningful data from smart devices’ sensors, especially, smartphones. In addition, different useful machine learning applications based on smartphones’ sensors data are shown. Moreover, different side channel attacks utilizing the same sensors and the same machine learning algorithms are overviewed.

Malware Detection Based on Deep Learning of Behavior Graphs

Abstract: The Internet of Things (IoT) provides various benefits, which makes smart device even closer. With more and more smart devices in IoT, security is not a one-device affair. Many attacks targeted at traditional computers in IoT environment may also aim at other IoT devices. In this paper, we consider an approach to protect IoT devices from being attacked by local computers. In response to this issue, we propose a novel behavior-based deep learning framework (BDLF) which is built in cloud platform for detecting malware in IoT environment. In the proposed BDLF, we first construct behavior graphs to provide efficient information of malware behaviors using extracted API calls. We then use a neural network-Stacked AutoEncoders (SAEs) for extracting high-level features from behavior graphs. The layers of SAEs are inserted one after another and the last layer is connected to some added classifiers. The architecture of the SAEs is 6,000-2,000-500. The experiment results demonstrate that the proposed BDLF can learn the semantics of higher-level malicious behaviors from behavior graphs and further increase the average detection precision by 1.5%.

Distributed Sensing Using Smart End-User Devices: Pathway to Federated Learning for Autonomous IoT

Abstract: There is a dearth of research in developing low-cost solutions for distributed decision making in IoT networks. Most studies in the literature require the deployment of additional sensors for data collection. In this study, we propose to leverage available sensors built-in smartphones, to properly collect and broadcast data for different decision-making purposes in smart cities infrastructures, for example, intelligent transportation networks, smart health services, security and emergencies, industrial control, smart agriculture, home automation and so on. To this end, we first introduce our new platform (including software and mobile app implementation) to identify available sensors at each end-user device. We have identified a wide range of sensors including gyroscope, ambient light sensor, temperature, magnetic field sensor, orientation sensor, game rotation vector, linear acceleration, relative humidity, gravity, geomagnetic rotation vector, etc. As the sensors are already integrated within the phone, therefore, using these sensors can be beneficial considering the complexity, efficiency, and cost of the overall system. The challenge is to design a system that can trigger distributed devices to be self-activated and agreed to generate all available sensors data. Besides, as devices can send a continuous stream of data, therefore, size of data could be mounted and could be in the haphazard structure, which would give us hurdles to identify a device sensor data from another and to make an intelligent decision. To tackle all of these, we propose a distributed sensing approach that is capable to identify a device using token, can activate distributed end-user devices to send data to the cloud whenever it requires and store data in the cloud server maintaining proper format. This approach enables remote data collection leveraging available end-user devices and reduces the cost of installing new sensors for autonomous IoT applications. We then build on our efficient sensing platform to enable distributed intelligence among a network of smart devices. To this end, we leverage the computational capacity of these devices for local decision making, i.e., instead of broadcasting all sensing information to a centralized agent and solve a large-scale decision-making problem, each smart device communicates with a limited set of neighboring devices. This will also pave the way for implementing federated learning as a promising solution for distributed decision making.

Session-Key Establishment and Authentication in a Smart Home Network Using Public Key Cryptography

Abstract: The development of the applications of Internet of Things (IoT) technology continues to grow steadily-one of the top applications being smart home environments. A smart home comprises digital devices and systems that operate inside a home to bring efficiency to home life. Devices with low computational ability and devices with high computational ability work together in a smart home network, and therefore, communication between devices needs to be secure. This article considers a lightweight and secure session-key establishment scheme for smart home networks and incorporates the Diffie-Hellman (DH) key exchange as an alternative method. A trusted service provider provides the algorithm parameters to the devices so that a public key can be established between the home gateway and a smart device. The proposed scheme is formally analyzed using Security Protocol Animator for Automated Validation of Internet Security Protocol and Applications (AVISPA).

Comments on “Biometrics-Based Privacy-Preserving User Authentication Scheme for Cloud-Based Industrial Internet of Things Deployment”

Abstract: Very recently, Das et al. (IEEE Internet of Things Journal, pp. 4900–4913, 5(6), DOI: 10.1109/JIOT.2018.2877690, 2018) presented a biometric-based solution for security and privacy in Industrial Internet of Things architecture. Das et al. claimed that their protocol is secure against known attacks. However, this comment shows that their protocol is defenseless against stolen verifier, stolen smart device, and traceability attacks. The attacker having access to public parameters and any of the verifier and parameters stored in smart device can easily expose the session key shared among the user and the smart device. Moreover, their protocol fails to provide perfect forward secrecy. Finally, this article also provides some necessary guidelines on attack resilience for the authentication schemes based on merely the symmetric key primitives, which are overlooked by Das et al.

One Voice Fits All?: Social Implications and Research Challenges of Designing Voices for Smart Devices

Abstract: When a smart device talks, what should its voice sound like? Voice-enabled devices are becoming a ubiquitous presence in our everyday lives. Simultaneously, speech synthesis technology is rapidly improving, making it possible to generate increasingly varied and realistic computerized voices. Despite the flexibility and richness of expression that technology now affords, today's most common voice assistants often have female-sounding, polite, and playful voices by default. In this paper, we examine the social consequences of voice design, and introduce a simple research framework for understanding how voice affects how we perceive and interact with smart devices. Based on the foundational paradigm of computers as social actors, and informed by research in human-robot interaction, this framework demonstrates how voice design depends on a complex interplay between characteristics of the user, device, and context. Through this framework, we propose a set of guiding questions to inform future research in the space of voice design for smart devices.

Middleware Implementation in Cloud-MANET Mobility Model for Internet of Smart Devices

Abstract: The smart devices are extremely useful devices that are making our lives easier than before. A smart device is facilitated us to establish a connection with another smart device in a wireless network with a decentralized approach. The mobile ad hoc network (MANET) is a novel methodology that discovers neighborhood devices and establishes connection among them without centralized infrastructure. Cloud provides service to the MANET users to access cloud and communicates with another MANET users. In this article, I integrated MANET and cloud together and formed a new mobility model named Cloud-MANET. In this Mobility model, if one smart device of MANET is able to connect to the internet then all smart devices are enabled to use cloud service and can be interacted with another smart device in the Cloud-MANET framework. A middleware acts as an interface between MANET and cloud. The objective of this article is to implement a middleware in Cloud-MANET mobility model for communication on internet of smart devices.

Robotic vacuum cleaners save energy? Raising cleanliness conventions and energy demand in Australian households with smart home technologies

Abstract: The ‘digital revolution’ of household life is underway, with technologies such as robotic vacuum cleaners (robovacs) increasingly common. Various other automated appliances are emerging and being adopted in pursuit of the ‘smart home’. Current discourses include assumptions and explicit claims that smart homes will be energy efficient and therefore more environmentally sustainable. However, smart home technologies are also presented as affording lifestyle enhancements in the areas of comfort, cleanliness, convenience, entertainment and security. Focusing specifically on one smart device – the robovac – this paper aims to demonstrate how visions of cleanliness in the smart home could be counterproductive to energy reductions and household wellbeing. We draw on a content analysis of smart home marketing and articles, and conversational interviews (involving home tours) with early adopters of robovacs and smart home technologies in Australia. We find that these devices may escalate conventions of cleanliness in the home and invite supplementary energy consumption. The paper concludes by providing suggestions for how energy stakeholders can respond.

Shake to Communicate: Secure Handshake Acceleration-Based Pairing Mechanism for Wrist Worn Devices

Abstract: With the booming penetration of wrist worn smart devices in daily lives, a wide range of applications have been enabled, such as exchanging social information, sharing sports data, and sending messages. Securing data exchange between these devices has become a challenging issue, considering the high security requirements and low computation capabilities of these wrist worn devices. In this paper, we propose a secure wrist worn smart device pairing scheme by exploiting the motion signal of the devices generated by the handshake to negotiate a reliable key between users. To ensure the security of key negotiation, a novel fuzzy cryptography algorithm is further developed. Compared with existing algorithms, the proposed algorithm avoids complicated error correction algorithms and has low requirements for data coincidence on the premise of individual differentiation. At the same time, the security is guaranteed by feature reordering and protection of auxiliary data. Extensive experimental results are provided, which demonstrate that the proposed handshake acceleration-based pairing scheme is robust, secure, and efficient.

Smart device usage in early childhood is differentially associated with fine motor and language development

Abstract: Aim We evaluated the relationships between the use of smart devices, such as smartphones and tablet computers, and the development levels and language scores in young children. Methods A cross-sectional analysis with 117 children aged three to five years was conducted. The participants were recruited from kindergartens in South Korea between November 2015 and April 2016. Parental questionnaires to assess smart device usage status by children, developmental screening test and receptive-expressive language scale were administered; metrics included smart device usage frequency and usage time, appropriate smart device usage level, developmental levels and language scores. Results Smart device usage frequency was significantly positively correlated with fine motor skill development [Spearman's correlation coefficient (rs ) = 0.426] in three-year-old children. Appropriate smart device usage level was also positively correlated with social development (rs = 0.466). However, smart device usage time was significantly negatively correlated with expressive language months (rs = -0.481). There were no such correlations in children aged four to five years. For the subcategories of appropriate usage level, the suitability of social relationship was significantly positively correlated with social development in three-year-old children (rs = 0.474). Conclusion In three-year-old children, smart device usage was positively correlated with fine motor development and negatively correlated with language development.

Understanding Motivators, Constraints, and Practices of Sharing Internet of Things

Abstract: Smart devices such as mobile phones, tablets, and smart watches are designed under the assumption that they will be used by a single user. In contrast, many other devices, such as smart thermostats and smart speakers, are inherently sharable. This paper presents results from a diary study that we conducted with 20 participants to gain a nuanced understanding of the purposes, motivators, and constraints involved in the sharing of smart devices, which are cumulatively referred to as the Internet of Things. We also report on users' practices of coordinating their shared use with sharees/co-users, the impact of not understanding a smart device's behavior and the context of shared use, the differences between sharing personal and inherently sharable devices in terms of content that is available and accessible, trust between sharees, and measures taken to ensure accountable use. Finally, we discuss the implications of our findings and provide guidelines for the design of future smart devices.

Light-Weight and Privacy-Preserving Authentication Protocol for Mobile Payments in the Context of IoT

Abstract: The widespread use of smart devices attracts much attention on the research for a mobile payment protocol in the context of the Internet of Things (IoT). However, payment trust and user privacy still raise critical concerns to the application of mobile payments since existing authentication protocols for mobile payments either suffer from the heavy workload on a resource-limited smart device or cannot provide user anonymity in the mobile payment. To address these challenges elegantly, this paper presents a lightweight and privacy-preserving authentication protocol for mobile payment in the context of IoT. First, we put forward a unidirectional certificateless proxy re-signature scheme, which is of independent interest. Based on this signature scheme, this paper, then, gives a new mobile payment protocol that for the first time not only achieves anonymity and unforgeability but also leaves low resource consumption on smart devices. In the proposed protocol, the efficiency is notably improved by placing the most computational cost on Pay Platform (usually with abundant computational power) instead of lightweight mobile devices. Moreover, by considering that the Pay Platform and Merchant Server needs to perform computation for each transaction, the idea of batch-verification has been adopted to mitigate the overhead for millions of users at the Pay Platform and Merchant Server to address the scalability issue. Through the formal security analysis presented in this paper, the proposed protocol is proved to be secure under the extended CDH problem. In addition, the performance evaluation shows that the proposed protocol is feasible and efficient for the resource-limited smart devices in the IoT.

Dynamic Social-Aware Computation Offloading for Low-Latency Communications in IoT

Abstract: Internet of Things (IoT) as a prospective platform to develop mobile applications, is facing with significant challenges posed by the tension between resource-constrained mobile smart devices and low-latency demanding applications. Recently, mobile edge computing (MEC) is emerging as a cornerstone technology to address such challenges in IoT. In this paper, by leveraging social ties in human social networks, we investigate the optimal dynamic computation offloading mode selection to jointly minimize the total tasks’ execution latency and the mobile smart devices’ energy consumption in MEC-aided low-latency IoT. Different from the previous studies, which mostly focus on how to exploit social tie structure among mobile smart device users to construct the permutation of all the feasible modes, we consider dynamic computation offloading mode selection with social awareness-aided network resource assignment, involving both the computing resources and transmit power from heterogeneous mobile smart devices. On the one hand, we formulate the dynamic computation offloading mode selection into the infinite-horizon time-average renewal-reward problems subject to time average latency constraints on a collection of penalty processes. On the other hand, an efficient solution is also developed, which elaborates on a Lyapunov optimization-based approach, i.e., drift-plus-penalty (DPP) algorithm. Numerical simulations are provided to validate the theoretical analysis and assess the performance of the proposed dynamic social-aware computation offloading mode selection method considering different configurations of the IoT network parameters.

Role of IoT in agriculture

Abstract: Today’s different type of technologies, techniques and tools are used in agriculture sector. To improve the productivity, efficiency and reduce the time, cost and human intervention, there is a need of new technology called as Internet of Things. To automate the agricultural activities like water management, soil monitoring, crop management, livestock monitoring etc. different types of sensor are used. Smart Greenhouse protect the plants from extreme weather. To control all these operations remote smart device, computer connected with internet, sensor, camera, micro-controller etc. are used. Growth in agriculture sector effects economic condition of the country. This paper focus on Role of IoT in Agriculture that defines Smart Farming.

Artificial Intelligence of Things Wearable System for Cardiac Disease Detection

Abstract: This study proposes an artificial intelligence of things (AIoT) system for electrocardiogram (ECG) analysis and cardiac disease detection. The system includes a front-end IoT-based hardware, a user interface on smart device’s application (APP), a cloud database, and an AI platform for cardiac disease detection. The front-end IoT-based hardware, a wearable ECG patch that includes an analog front-end circuit and a Bluetooth module, can detect ECG signals. The APP on smart devices can not only display users’ real-time ECG signals but also label unusual signals instantly and reach real-time disease detection. These ECG signals will be uploaded to the cloud database. The cloud database is used to store each user’s ECG signals, which forms a big-data database for AI algorithm to detect cardiac disease. The algorithm proposed by this study is based on convolutional neural network and the average accuracy is 94.96%. The ECG dataset applied in this study is collected from patients in Tainan Hospital, Ministry of Health and Welfare. Moreover, signal verification was also performed by a cardiologist.

Secure Your Voice: An Oral Airflow-Based Continuous Liveness Detection for Voice Assistants

Abstract: Voice control has attracted extensive attention recently as it is a prospective User Interface (UI) to substitute for conventional touch control on smart devices. Voice assistants have become increasingly popular in our daily lives, especially for those people who are visually impaired. However, the inherently insecure nature of voice biometrics means that voice assistants are vulnerable to spoofing attacks as evidenced by security experts. To secure the commands for voice assistants, in this paper, we present a liveness detection system that provides continuous speaker verification on smart devices. The basic aim is to match the voice received by the smart device's microphone with the oral airflow of the user when speaking a command. The airflow is captured by an auxiliary commercial off-the-shelf airflow sensor. Specifically, we establish a theoretical model to depict the relationship between the oral airflow pressure and the phonemes in users' speech. The system estimates a series of pressures from the speech according to the theoretical model, and then calculates the consistency between the estimated pressure signal and the actual pressure signal measured by the airflow sensor to determine whether a command is a genuine "live" voice or an artificially generated one. We evaluate the system with 26 participants and 30 different voice commands. The evaluation showed that our system achieves an overall accuracy of 97.25% with an Equal Error Rate (EER) of 2.08%.

Removal of Oil Spills through a Self‐Propelled Smart Device

Abstract: Oil/water separation through superhydrophobic/superoleophilic materials has attracted considerable interest over the past decades; however, dealing with oil spills on broad waters through an active way remains a challenge. Herein, we report a self-propelled smart device driven by the decomposition of hydrogen peroxide that can spontaneously move on the water surface and collect floating oil droplets inside with superhydrophobic and superoleophilic properties. Moreover, the self-propelled smart device exhibits excellent stability and high efficiency for oil/water separation. We believe this study may provide a promising strategy for fabricating smart aquatic devices that have potential applications in water remediation.

Conceptual Framework of Smart Device for Smart Home Management Based on RFID and IoT

Abstract: World population is expanding continuously; the current world population is more than seven billion. And approximately 65–70% of the total population by 2050 will be in urban cities. This has also given a significant rise in the concept of Smart cities. To keep a pace with this fast moving life, Smart city provides equilibrium. With the fast moving world the life of human also became very fast which comes with lots of daily problems too. People forget where they placed their things. Daily life becomes a mess to many people nowadays. Our paper is an attempt to provide a design of a smart device which will help user for day to day memory management. A device, which will coordinate the help of RFID and IOT to recognize every second in a day. The methodology of the same paper talks about RFID and sensor-based object and one central device coordination. Once you put it on and it tracks everything, analyses everything and tells you where your object was kept last. This device will be very helpful especially for patients suffering from memory loss problems. Memory is a problem to all and the device can help out in this busy world.

Logical Tree Based Secure Rekeying Management for Smart Devices Groups in IoT Enabled WSN

Abstract: With the rapid growth in a huge number of devices connecting online, Internet of Things (IoT) is rapidly growing and getting interested of researchers. IoT enabled wireless sensor network (WSN) plays a significant role to collect sensing data and transmit to central repositories. Moreover, multicasting ensures efficient group communication for disseminating the same query or command to all smart devices to perform mobile service computing. It is applicable in the smart home, healthcare, smart cities, and smart industries for monitoring and control. To secure such sensitive information exchange, we have considered a secure group communication scenario where logical trees are maintained for each group. The main problem is unnecessary rekeying when a smart device frequently joining or leaving the network. It causes computation, communication, and energy overheads. To overcome the excessive rekeying problem, we have presented a logical tree-based secure mobility management scheme (LT-SMM) using mobile service computing in IoT. It includes the group deployment phase where smart devices securely setup a group by registering with group heads for future secure information exchange. We have presented group deployment, mobile node joining and mobile node migration protocols. Moreover, we have used chaotic map based one-way hash functions to ensure message integrity. To validate our work, extensive simulations are performed using NS 2.35. TCL code is used to configure smart devices, deploy logical tree, messaging. C language is used for algorithm implementation and messaging backend coding. The results verify the supremacy of our scheme as compared to existing tree based schemes in terms of computation, communication, and energy consumption.

Scalable and Forward Secure Network Attestation With Privacy-Preserving in Cloud-Assisted Internet of Things

Abstract: To ensure the normal work of the whole system in the context of the Internet of Things (IoT), remote attestation for each smart device should be guaranteed. However, considering the huge number of smart devices, the traditional individual attestation schemes cannot meet the requirements in terms of efficiency. In addition, protecting the sensitive identity information related to the devices also needs to be supported. Furthermore, avoiding security risks caused by the secret key exposures is very important in the context of the IoT, where the compromise of terminal devices frequently occurs. To solve these challenges, in this paper, we present a new network attestation scheme that, for the first time, provides scalability, forward-security, and privacy preserving simultaneously. The new scheme allows anyone to publicly verify a collective attestation, and any identity information of the provers will not be revealed to the verifier. Moreover, it provides unforgeability and confidentiality of the previous messages even though the current secret key is exposed. Considering the limited resources of lightweight devices in the context of the IoT, our scheme outsources the main computational task to an untrusted cloud server. Finally, our security proof and performance evaluation show that our scheme is secure and feasible.

A Smart Irrigation System to Automate Irrigation Process Using IOT and Artificial Neural Network

Abstract: In the today's world we are growing towards the automation of day to day daily life task in which we are focused on creation of smart cities, smart home etc. which includes a lot of work which deals with automation of task using Artificial Intelligence, Internet of Things and machine Learning. These technologies are widely used to creates a system for automation of different tasks. In this technology driven society there is a need of creation of a system to automate the process of irrigation of crops to help farmers. The currently used system includes a lot of human efforts, money and time which will not be required after the development of an automated irrigation system. In this there is a need of creating a system which can collect data then analyze that date and generate results in real time. also, the overall cost should be low enough so that a farmer can afford it. In this paper we are focusing on creating a low-cost smart device which can be used to collect the data of moisture in soil at different places, pH and temperature of soil. We focus of creating a device with Arduino along with some sensors and modules to collect these data at different places in farm. After collecting this data this device will send this data to server with the help of a Wi-Fi module attached to the device. At the same time, we are using an Artificial Neural Network model for the analysis of this data for generating high accuracy results. Finally based on the results the device triggers a valve to automatically start and stop the flow of water in the farm.

IoT for 5G/B5G Applications in Smart Homes, Smart Cities, Wearables and Connected Cars

Abstract: Internet of things (IoT) is referred to as smart devices connected to the internet. A smart device is an electronic device, which may connect to other devices or are part of a network such as Wi-Fi. The increase of IoT devices has helped with advancing technology in many areas of society. Application of IoT in 5G/B5G devices has provided many benefits such as providing new ideas that can become projects for tech companies, generating big data (large volume of data which can be used to reveal trends, patterns and associations) and providing various ways of communicating. This has also had an impact on how companies improve their business with the use of advanced technology. However, the rapid growth of IoT has introduced a new platform for cybercriminals to attack. There has been published security measures on IoT to help deal with such risks and vulnerabilities. This survey paper will explore IoT in relation to smart homes, smart cities, wearables and connected cars. The benefits, risks and vulnerabilities will be discussed that comes along with using such devices connected to the internet.

A Smart Device System to Identify New Phenotypical Characteristics in Movement Disorders.

Abstract: Parkinson’s disease and Essential Tremor are two of the most common movement disorders and are still associated with high rates of misdiagnosis. Collected data by technology-based objective measures (TOMs) has the potential to provide new promising and highly accurate movement data for a better understanding of phenotypical characteristics and diagnostic support. A technology-based system called Smart Device System (SDS) is going to be implemented for multi-modal high-resolution acceleration measurement of patients with PD or ET within a clinical setting. The two-year prospective observational study is conducted to identify new phenotypical biomarkers and train an Artificial Intelligence System. The SDS is going to be integrated and tested within a 20-minutes assessment including smartphone-based questionnaires, two smartwatches at both wrists and tablet-based Archimedean spirals drawing for deeper tremor-analyses. The electronic questionnaires will cover data on medication, family history and non-motor symptoms. In this paper, we describe the steps for this novel technology-utilizing examination, the principal steps for data analyses and the targeted performances of the system. Future work considers integration with Deep Brain Stimulation, dissemination into further sites and patient’s home setting as well as integration with further data sources as neuroimaging and biobanks. Study Registration ID on ClinicalTrials.gov: NCT03638479.

Age of information of two-way data exchanging systems with power-splitting

Abstract: We consider a two-way data exchanging system consisting of an access point and a smart device The access point has a constant power supply and the smart device does not The access point simultaneously transmits information and energy to the smart device over block fading channels, with fixed powers Pt and Pt, respectively The smart device receives data and energy at the same time, and stores the harvested energy in an energy buffer Upon collecting enough energy, the smart device performs one block of transmission immediately We investigate the timeliness and the efficiency of the system in terms of age of information (AoI) and data rate, respectively We also investigate the trade-off between downlink communications and uplink communications by optimizing the weighted-sum average AoI and weighted-sum data rate Moreover, we present the optimal power-splitting ratio p and the optimal weighting coefficient w explicitly or via efficient algorithm

IoT Based Smart Energy Metering System for Power Consumers

Abstract: Smart devices are growing in the latest years, enabling smart cities to be built. A smart city is focused on a smart grid that enables intelligent management of the electric grid. To make this happen, the network must have smart meters capable of duplex communication with the network. This industry has resulted in a spread of intelligent meters providing a chance to assess the consumption of each unit in households. The aim of this initiative is to create a popular chip based IoT electrical meter that will capture all meter information and transmit the required meter information to the main server by means of wireless communication. In the main server, all meter information will be handled, and the required choices will be made using the main server. Regarding pending fees, the server would inform the customer and then disconnect the line if needed. In cases of tampering, the server would respond immediately and sever the line. Experimental findings in this work demonstrate the accuracy of the readings produced using the smart device created.

Smart Assistance for Students and People Living in a Campus

Abstract: Being part of one of the fastest growing area in Artificial Intelligence (AI), virtual assistants are nowadays part of everyone's life being integrated in almost every smart device. Alexa, Siri, Google Assistant, and Cortana are just few examples of the most famous ones. Beyond these off-the-shelf solutions, different technologies which allow to create custom assistants are available. IBM Watson, for instance, is one of the most widely-adopted question-answering framework both because of its simplicity and accessibility through public APIs. In this work, we present a virtual assistant that exploits the Watson technology to support students and staff of a smart campus at the University of Palermo. Some in progress results show the effectiveness of the approach we propose.

Does public service delivery through new channels promote citizen trust in government? The case of smart devices*

Abstract: From the government’s perspective, it is important to understand the factors that influence effective utilization of new service channels, particularly the use of smart devices. Furthermore, how th...