Intelligent Energy Optimization for User Intelligible Goals in Smart Home Environments

Intelligent management of energy consumption is one of the key issues for future energy distribution systems, smart buildings, and consumer appliances. The problem can be tackled both from the point of view of the utility provider, with the intelligence embedded in the smart grid, or from the point of view of the consumer, thanks to suitable local energy management systems (EMS). Conserving energy, however, should respect the user requirements regarding the desired state of the environment, therefore an EMS should constantly and intelligently find the balance between user requirements and energy saving. The paper proposes a solution to this problem, based on explicit high-level modeling of user intentions and automatic control of device states through the solution and optimization of a constrained Boolean satisfiability problem. The proposed approach has been integrated into a smart environment framework, and promising preliminary results are reporte

Publishing LO(D)D: Linked Open (Dynamic) Data for Smart Sensing and Measuring Environments

The paper proposes a distributed framework that provides a systematic way to publish environment data which is being updated continuously; such updates might be issued at specific time intervals or bound to some environment- specific event. The framework targets smart environments having networks of devices and sensors which are interacting with each other and with their respective environments to gather and generate data and willing to publish this data. This paper addresses the issues of supporting the data publishers to maintain up-to-date and machine understandable representations, separation of views (static or dynamic data) and delivering up-to-date information to data consumers in real time, helping data consumers to keep track of changes triggered from diverse environments and keeping track of evolution of the smart environment. The paper also describes a prototype implementation of the proposed architecture. A preliminary use case implementation over a real energy metering infrastructure is also provided in the paper to prove the feasibility of the architectur

Spamming the Internet of Things: A Possibility and its probable Solution

AbstractThe Internet of Things (IoT) enabled users to bring physical objects into the sphere of cyber world. This was made possible by different tagging technologies like NFC, RFID and 2D barcode which allowed physical objects to be identified and referred over the Internet. Due to less complexity and low development and deployment cost of 2D barcodes, they have become modus operandi for building an IoT system. This paper explores the possibility of spamming the Internet of Things. It tries to establish that web spammers can use 2D barcodes to flood the physical side of the IoT, trick users to see or reach unsolicited and unrelated content over the Internet and possibly destroy the legitimacy of correct content. Preliminary results from an experiment establishing the possibility of the problem are outlined. This paper also proposes the use of digital signatures (ECDSA) to address the problem of spamming the IoT. A prototype implementation of the solution and its experimental results are given in this paper

Enabling Machine Understandable Exchange of Energy Consumption Information in Intelligent Domotic Environments

In the 21st century, all the major countries around the world are coming together to reduce the impact of energy generation and consumption on the global environment. Energy conservation and its efficient usage has become a top agenda on the desks of many governments. In the last decade, the drive to make homes automated and to deliver a better assisted living picked pace and the research into home automation systems accelerated, usually based on a centralized residential gateway. However most devised solutions fail to provide users with information about power consumption of different house appliances. The ability to collect power consumption information can lead us to have a more energy efficient society. The goal addressed in this paper is to enable residential gateways to provide the energy consumption information, in a machine understandable format, to support third party applications and services. To reach this goal, we propose a Semantic Energy Information Publishing Framework. The proposed framework publishes, for different appliances in the house, their power consumption information and other properties, in a machine understandable format. Appliance properties are exposed according to the existing semantic modeling supported by residential gateways, while instantaneous power consumption is modeled through a new modular Energy Profile ontolog

Real-Time Monitoring of High-Level States in Smart Environments

Modern smart environments are equipped with a multitude of devices and sensors aimed at intelligent services. The presence of these diverse devices has raised a major problem of managing complex environments. A rising solution to the problem is the modeling of user goals and intentions, and then interacting with the respective smart environments using user defined goals. Generally, the solution advocates that the user goal(s) can be represented by combining devices (smart appliances and sensor/actuators) in particular states. `Domotic Effects' is a high level modeling approach, which provides Ambient Intelligence (AmI) designers and integrators with a high level abstract layer that enables the definition of user goals in a smart environment, in a declarative way, which can be used to design and develop intelligent applications. This paper describes an approach for the automatic evaluation of domotic effects combined through Boolean expressions, that can provide efficient and intelligent monitoring of the domotic structure of the environment. ``Effects Evaluation'' addresses the problem of finding the new values of all the domotic effects defined for the environment when one or more devices change their state or one or more sensor value is recorded in the environment, hence determining a new overall state of the environment. The paper also presents an architecture to implement the evaluation of domotic effects. Results obtained from carried out experiments prove the feasibility of the approach and highlight responsiveness of the implemented effect evaluation

SAT based Enforcement of Domotic Effects in Smart Environments

The emergence of economically viable and efficient sensor technology provided impetus to the development of smart devices (or appliances). Modern smart environments are equipped with a multitude of smart devices and sensors, aimed at delivering intelligent services to the users of smart environments. The presence of these diverse smart devices has raised a major problem of managing environments. A rising solution to the problem is the modeling of user goals and intentions, and then interacting with the environments using user defined goals. `Domotic Effects' is a user goal modeling framework, which provides Ambient Intelligence (AmI) designers and integrators with an abstract layer that enables the definition of generic goals in a smart environment, in a declarative way, which can be used to design and develop intelligent applications. The high-level nature of domotic effects also allows the residents to program their personal space as they see fit: they can define different achievement criteria for a particular generic goal, e.g., by defining a combination of devices having some particular states, by using domain-specific custom operators. This paper describes an approach for the automatic enforcement of domotic effects in case of the Boolean application domain, suitable for intelligent monitoring and control in domotic environments. Effect enforcement is the ability to determine device configurations that can achieve a set of generic goals (domotic effects). The paper also presents an architecture to implement the enforcement of Boolean domotic effects, and results obtained from carried out experiments prove the feasibility of the proposed approach and highlight the responsiveness of the implemented effect enforcement architectur

Cardiopulmonary resuscitation: outcome and its predictors among hospitalized adult patients in Pakistan.

Introduction:Our aim was to study the outcomes and predictors of in-hospital cardiopulmonary resuscitation (CPR) among adult Patients at a tertiary care centre in Pakistan.Methods:We conducted a retrospective chart review of all adult Patients (age \u3e or =14 years), who underwent CPR following cardiac arrest, in a tertiary care hospital during a 5-year study period (June 1998 to June 2003). We excluded Patients aged 14 years or less, those who were declared dead on arrival and Patients with a do not resuscitate order. The 1- and 6-month follow-ups of discharged Patients were also recorded.Results:We found 383 cases of adult in-hospital cardiac arrest that underwent CPR. Pulseless electrical activity was the most common initial rhythm (50%), followed by asystole (30%) and ventricular tachycardia/fibrillation (19%). Return of spontaneous circulation was achieved in 72% of Patients with 42% surviving more than 24 h, and 19% survived to discharge from hospital. On follow-up, 14% and 12% were found to be alive at 1 and 6 months, respectively. Multivariable logistic regression identified three independent predictors of better outcome (survival \u3e24 h): non-intubated status [adjusted odds ratio (aOR): 3.1, 95% confidence interval (CI): 1.6-6.0], location of cardiac arrest in emergency department (aOR: 18.9, 95% CI: 7.0-51.0) and shorter duration of CPR (aOR: 3.3, 95% CI: 1.9-5.5).Conclusion:Outcome of CPR following in-hospital cardiac arrest in our setting is better than described in other series. Non-intubated status before arrest, cardiac arrest in the emergency department and shorter duration of CPR were independent predictors of good outcome

Higher entropy observed in SARS-CoV-2 genomes from the first COVID-19 wave in Pakistan

Background: We investigated the genome diversity of SARS-CoV-2 associated with the early COVID-19 period to investigate evolution of the virus in Pakistan.Materials and methods: We studied ninety SARS-CoV-2 strains isolated between March and October 2020. Whole genome sequences from our laboratory and available genomes were used to investigate phylogeny, genetic variantion and mutation rates of SARS-CoV-2 strains in Pakistan. Site specific entropy analysis compared mutation rates between strains isolated before and after June 2020.Results: In March, strains belonging to L, S, V and GH clades were observed but by October, only L and GH strains were present. The highest diversity of clades was present in Sindh and Islamabad Capital Territory and the least in Punjab province. Initial introductions of SARS-CoV-2 GH (B.1.255, B.1) and S (A) clades were associated with overseas travelers. Additionally, GH (B.1.255, B.1, B.1.160, B.1.36), L (B, B.6, B.4), V (B.4) and S (A) clades were transmitted locally. SARS-CoV-2 genomes clustered with global strains except for ten which matched Pakistani isolates. RNA substitution rates were estimated at 5.86 x10-4. The most frequent mutations were 5\u27 UTR 241C \u3e T, Spike glycoprotein D614G, RNA dependent RNA polymerase (RdRp) P4715L and Orf3a Q57H. Strains up until June 2020 exhibited an overall higher mean and site-specific entropy as compared with sequences after June. Relative entropy was higher across GH as compared with GR and L clades. More sites were under selection pressure in GH strains but this was not significant for any particular site.Conclusions: The higher entropy and diversity observed in early pandemic as compared with later strains suggests increasing stability of the genomes in subsequent COVID-19 waves. This would likely lead to the selection of site-specific changes that are advantageous to the virus, as has been currently observed through the pandemic

Diagnosis of enteric fever in the emergency department: a retrospective study from Pakistan

Background:Enteric fever is one of the top differential diagnoses of fever in many parts of the world. Generally, the diagnosis is suspected and treatment is initiated based on clinical and basic laboratory parameters.Aims: The present study identifies the clinical and laboratory parameters predicting enteric fever in Patients visiting the emergency department of a tertiary care hospital in Pakistan.Methods:This is a retrospective chart review of all adult Patients with clinically suspected enteric fever admitted to the hospital through the emergency department during a 5-year period (2000-2005).Results:A total of 421 emergency department Patients were admitted to the hospital with suspected enteric fever. There were 53 cases of blood culture-positive enteric fever and 296 disease-negative cases on culture. The mean age in the blood culture-positive group was 27 years (SD: 10) and in the group with negative blood culture for enteric fever, 35 years (SD: 15) with a male to female ratio of 1:0.6 in both groups. Less than half (48%) of all Patients admitted with suspected enteric fever had the discharge diagnosis of enteric fever, of which only 13% of the Patients had blood culture/serologically confirmed enteric fever. None of the common clinical and laboratory parameters differed between enteric fever-positive Patients and those without it.Conclusion:Commonly cited clinical and laboratory parameters were not able to predict enteric fever