Pervasive Computing - Science topic

Ambient Intelligence (AmI) and Internet of Things (IoT) are two concepts that have gained significant attention in the field of technology. While they share some similarities, there are also distinct differences between the two.

Ambient Intelligence refers to a computing environment that is sensitive and responsive to human presence. It aims to create an intelligent and intuitive system that can adapt to users' needs without explicit instructions. AmI systems utilize sensors, data analysis, and machine learning algorithms to provide personalized services in a seamless manner. For example, smart homes equipped with AmI technology can adjust lighting, temperature, and music preferences based on individual preferences.

On the other hand, the Internet of Things refers to a network of physical objects embedded with sensors, software, and connectivity capabilities. IoT enables these objects to collect and exchange data over the internet without human intervention. The main goal of IoT is to connect various devices for efficient communication and automation. For instance, IoT can be seen in applications like smart cities where streetlights automatically adjust their brightness based on real-time traffic conditions.

Although both AmI and IoT involve interconnected devices and rely on data collection for decision-making processes, there are key differences between them. Firstly, while AmI focuses on creating an intelligent environment that adapts to humans' needs seamlessly, IoT emphasizes connecting devices for efficient communication without direct human involvement.

Secondly, AmI systems primarily rely on local processing capabilities within the environment itself. This means that most of the data processing occurs within the immediate vicinity of users or devices. In contrast, IoT systems often rely on cloud computing for storing and analyzing large amounts of data collected from multiple sources.

Lastly, another difference lies in their scope of application. Ambient Intelligence has a more personal focus as it aims at providing personalized services tailored specifically for individuals or small groups. On the other hand, IoT has broader applications ranging from industrial automation to healthcare monitoring systems.

In conclusion, Ambient Intelligence (AmI) and Internet of Things (IoT) are two distinct concepts in the field of technology. While they share similarities in terms of interconnected devices and data collection, their focus, processing capabilities, and scope of application differ significantly. Both concepts have the potential to revolutionize various industries and improve our daily lives.

Reference:

Kidd, C.D., Orr, R.J., Abowd, G.D., Atkeson, C.G., Essa, I.A., MacIntyre, B., Mynatt E.D. & Starner T.E. (1999). The Aware Home: A Living Laboratory for Ubiquitous Computing Research. In Proceedings of the Second International Workshop on Cooperative Buildings (CoBuild '99), 191-198.

Use

Same idea can be found in springers and other publishers

Multiagent and Gird systems by IOS press.

EAI Transaction on scalable information systems

EAI Transaction on Cloud

IEEE Transaction on Cloud Computing

I think that a very relevant subject is how mobile computing and pervasive environment can support information access to people with disabilities.

You may check this extensive research work (Pervasive Computing Reference Architecture from a Software Engineering Perspective).  Please check for the security quality feature.    You may check this interesting  article as well that shows security penetration test results by HP.

D. Storm, “Of 10 IoT-connected home security systems tested, 100% are full of security FAIL,” COMPUTERWORLD, 11-Feb-2015.

You may find the following papers useful.

1) Prekop, Paul, and Mark Burnett. "Activities, context and ubiquitous computing." Computer Communications 26.11 (2003): 1168-1176.

2) Henricksen, Karen, Jadwiga Indulska, and Andry Rakotonirainy. "Modeling context information in pervasive computing systems." Pervasive Computing. Springer Berlin Heidelberg, 2002. 167-180.

3) Manzoor, Atif, Hong-Linh Truong, and Schahram Dustdar. "Quality of context: models and applications for context-aware systems in pervasive environments." The Knowledge Engineering Review 29.02 (2014): 154-170.

 Ed, I think that you have an interesting question here.  There are numerous indoor activities that could benefit from more fine-grained position awareness (trade shows, conferences, schools, etc.) and I think that it is just a matter of time before we see more and more iBeacons around.  The question that I have about this is the logistics of maintaining the infrastructure.  Any kind of sensor needs power and even with the best battery life that we currently have there is a fairly short time limit for the utility of the beacon.  If we start "throwing" lots of these into the environment what will the near future look like when the batteries start to fail?  I see some work on the use of these sensors and beacons but have not seen much on the long term prospects for the technology - IMHO this will be a big issue for Internet of Things.

From my perspective, working in a related field, the most important question is why you need emotion sensing systems? If the answer is because you want to improve health, then that is the challenge, not the sensing systems as systems, but the success of the health improving interventions. And then the challenge become, how one create good health interventions, how do one stop the destructive behavior and motivate the health improving behavior. Here I think social and cultural aspects, long time behavior and learning/mastery curves is important.

What cultural and social values do the system promote and reproduce?

How do one maintain the health improving behavior over time?

How do one create good and challenging learning and mastery experiences (curves) over time?

In our project RHYME we create multi-sensory Internet of Things (interactive MSE) to motivate social and aesthetic co-creation for children with severe disabilities and their families. Here we use musical improvisation (advanced musical algorithms) and sensory stimulation to motivate social co-creation (positive and equal creative behavior that promote both aesthetical experiences and musical mastery). 

Both Abstractions can work on top of the transport layer.Data centric approach can be more beneficial due to cache and repository (permanent storage). In DTN the node will always go towards the source to get the answer, but in data centric any intermediary node can also send the data back to the requester.According to Dr.Kevin(DTNRG IETF chair) both abstractions are evolving. Since there are different scenarios in Challenged Networks, at the end it boils down which one is more suitable to your scenario, and on which abstraction which have to work less to port your scheme.   You may want to look at this thread in the ICNRG group where different networking researchers are answering the subset of this question .(http://www.ietf.org/mail-archive/web/icnrg/current/msg00261.html)

Dear friends,

please find attached a summary of the results of the survey on Social IoT, which you also participated in. I hope you find the resulting information useful to your research work. I thank you once again for your help. The survey is still online and I will upload updated results to the web site www. social-iot.org.

Hello Jonas Mellin,

here i have added some information based WSN's, Please go through these point it may helps you,

Monitoring health care system

The main features of a monitoring system that integrates the HCCAC (Health Care Context-Aware Computing) architecture and wireless sensor networks and is aimed at improving healthcare of dependent people. The HCCAC system is based on a multi-agent architecture that is comprised of various types of intelligent agents. The primary agent in HCCAC is the Interpreter Agent, which is integrated into the system. The purpose of this agent is to provide solutions for the well being of the user through the use of action plans based on the information provided by the WSN sensors.

The most important characteristics of the system are:

(i) the Interpreter Agent has reasoning capability; it can analyze and reason the context data gathered by the system and provide proactive solutions,

(ii) the Interpreter Agent can easily adapt to the context within which it acts,

(iii) gather sensor data and messages from other agents in order to provide efficient solutions and

(iv) the Interpreter Agent performs a data fusion with the information received.

The system uses several WSNs in order to automatically gather context information. Based on the data received by the WSNs, the Interpreter agent fuses, evaluates and reasons the data in order to develop action plans and initiate events that affect the sensors that are also connected in the WSNs.

and please go through herewith the attached file.

The IOT, big data, and ubiquitous computing will I predict introduce untold complexity, as humans respond to immersion in situations of actual or possible ubiquitous monitoring with real time data analysis across real and cyber worlds. One vision is that humans may attempt to adapt and learn responses and controls, perhaps even focusing on engineering bio and profiling outputs readable by sensors. There may be an increased movement to switch off or seek invisibility as privacy becomes a more desirable and less accessible attribute. Data destruction or disruption may be an optional feature. Generic 'types' of identities based on similar groups of people may be preferred by users rather than personalization. Technologies that could allow humans to negotiate and have visibility to control and monitor their own attention, interactions, preferences and predictive patterns in the sea of technologies and networks will be in demand I think. Context aware apps may be device independent, with users flipping identities for different aspects of interactions in different situations. New challenges will be for trustworthy reliable technologies adapt at negotiating control and autonomy between individuals, communities and environments. Energy harvesting will be huge.

You might want to take a look at DiaSim. It is a smart home/office simulator.

DiaSim is, in turn, based on context simulator Siafu. Siafu looks abandoned, but still might be of use to you.

May be something like sixth sense by pranav mistry? Http://www.pranavmistry.com/projects/sixthsense/

Here is another nice online article 5 under the title "Things About Ubiquitous Computing That Make Me Nervous" by Anne Galloway,

Hi Ali,

Those terms are interchangeable in many sides in the way the community deals with them. Recently, the most popular conferences in those two areas, Pervasive and Ubicomp, are joined with each other starting from 2013 and the joined conference "UbiComp" will be held in Zurich.

They both refer to the growing trend towards embedding technology in everyday objects so they can communicate information.  The words pervasive and ubiquitous mean "existing everywhere." Pervasive computing devices are completely connected and constantly available. 

I should also point that in his work (Lyytinen, 2003) made a major distinguish between those two concepts by comparing both in terms on mobility and embeddedness. In his work, both pervasive and ubiquitous computing are of high embeddedness but ubiquitous has a higher mobility.