The notion of “network” can be defined in very different ways, which depends on whether it is taken in a more specific or a wider sense. They can be described as systems where elements and nodes are connected with each other exchanging information in short periods [43] or in real time. The definition comprises not only sociological but also technological matters. Elements and nodes can be represented by many things: individuals in a social context as well as components in a high-tech platform. One node can be part of one or many networks at once and in the Smart city it is required to develop complex structured networks to take advantage of the data and perform on time data analytics to balance and organize the exchange of the energy flows [44].

Thinking of a pre-Internet era the network was limited to fixed and mobile telephony, faxes and text messages through the Short Message Service (SMS). The first step ahead was the World Wide Web (WWW), enabled by adding smartness to the network, which primary focus was the sharing of contents (Google 1998). Adding smartness to Information Technologies (IT) platforms and services the WWW has evolved in the WEB 2.0 in which the focus was to provide services through the network. In the early 2000s the smartness in phones and applications raises and the focus of the network moved to allowing people to be connected through the social media (Facebook 2004, Twitter 2006, iPhone 2007).

The evolution step that can be noticed today is triggered by the rise of smartness inside the devices which are permeating the everyday life. The focus now is mainly directed to a machine-to-machine level of communication (identification, tracking, monitoring, metering) [45] commonly addressed as the IoT [46]. The huge amount of data collected by IoT systems enables the pervasive use of machine learning algorithms [47]. The consequent integration of Artificial Intelligence (AI) systems into the network, will allow data evaluation on a big scale [48], trying to bridge the problem of unstructured data that are a huge amount of unusable information and a grey quantity of information which is redundant and with no added value.

It is possible to benefit from the described technological progress and apply it to the abandoned island of Poveglia with the aim to turn Poveglia Island into a node within a broader university network that has an impact both on the digital as well as on the physical world as Cognitive Campus (Figure 1).

Figure 1.

Vision of a Cognitive Campus network with Poveglia as a node of the network

The Cognitive Campus principle is transferred by the Smart campus of the University of Brescia which is the first national experience in this direction.

In this University Campus a local smart grid is providing energy to the buildings and the pilot building eLUX lab has been used as a demonstrator of technologies for renewable energy production, green vehicle electricity supply, learning spaces equipped with sensors to monitor the indoor comfort conditions and enable control actuations to increase the real time responsiveness of the building. A probabilistic approach to evaluate the users’ influence on energy consumption of the building has been implemented and tested [49]-[51]. The Cognitive Campus Network extends the management at campus level to increase the scale of the intervention and broaden the possibility to connect and to utilize the resources of knowledge distributed in the network. The idea is to have all the buildings that can interact with the users and between them to communicate useful information to servitize the daily activities of the users/students with the goal to increase the learning engagement, proficiency, wellbeing, health, security and social improvement.

Cognitive Buildings respond to changes imposed by external and internal variables such as climate or user behaviour, optimizing processes that influence the overall performance of the building, considering the comfort issues and the environmental impact. The idea of Cognitive Campus goes beyond and envisions the combination of several Cognitive Buildings into a network in which IoT technologies are combined with AI agents to achieve a dialogue between buildings and end-users as well as between one building and another. The key elements of a cognitive process involve understanding, reasoning and learning. Computers are nowadays able to handle large volumes of structured and unstructured data, analyse it and generate outputs that are “conscious” of the evolutions of the problem. One of the most advanced examples of such an AI system is currently coming from researchers of IBM who have developed the cognitive agent Watson [52] able to process big data and it received the higher scores in information ingestion, inter intelligence, relevancy intelligence and tuning criteria compared to other similar tools and it is able to give value to the amount of dark data generated and often unexploited. The users data are not always clear and the use of AI to analyze and explore the feedback has a relevant impact on how to renspond to their needs and expectations. For example in the Customer eXperince (CX) in which Watson is now widely adopted, it is possible to identify the positive-negative sentiment to delineate positive and negative experiences contained in the same feedback comments or other data sources. This would revolutionaze the possibility to interpret and renspond to the users’ requests (directly or indirectly formulated).

The research programme of eLux at the University of Brescia, deals with the idea to integrate Watson as part of the cognitive concept for the Smart campus. This idea has been the base concept from which the project “Maritime Oasis” for Poveglia has been developed [36]. As an example, in the eLux Cognitive Building, sensors are used to control the indoor air quality and number of people related to prevent high levels of CO₂ concentration that is obstructing both an optimal cognitive and learning performance and wellbeing. The sensors are gathering data which are processed and analysed to produce a deep knowledge of the building management and use of the spaces made by the students and the activation of actuators to eventually provide additional ventilation is based on the gathered information about the concerned devices [53] such as Air Handling Unit (AHU) fan controls, windows opening, Indoor Air Quality (IAQ) indicators, etc. The further step of the cognitive process is to predict when the critical conditions will be registered based on the historical series of data and set up of the fan and ventilation to prevent the issue (Figure 2).

In Maritime Oasis, Watson can be employed to analyse the collected information from both the built environment and the end-users through web App. AI systems could analyse measures and feedbacks to select the suitable instructions for actions that adjust the buildings to react towards users’ needs and preferences.

Figure 2.

Cumulative curve of CO₂ concentration and sample day where temperature and relative humidity are plotted with n. people

The aim is to integrate users and their behaviour into an overall self-managing building system. Latter is passing through an appropriate infrastructure up to the computation centre that organizes and evaluates the incoming data. Subsequently, the computation centre triggers the actuators. The aim is to endorse the enhancement of the conditions to improve living quality and UX while saving energy and possibly reach the load matching of the renewable energy production and the electrical use of the building. In this direction the integration of vehicles for green mobility into the University Campus to act as storage is exemplified [54].

Applied to architecture this would translate into smart buildings that aggregate into a common network. The ubiquitous computing agent which analyses all the data collected from various sensors maximizes their potentials. All the users involved in this network will be able to send their feedback directly to Watson. Such feedback is considered for the building automation, whereas the system can deduce certain patterns of behaviours. Throughout forecasts the system can predict the necessary changes for the building performance and consider external factors [55] (i.e., weather station data, green vehicle pattern use, predicted occupancy based on weekly schedule, etc.). Either in real time or in a programmed time period, the actuators that control part of the buildings will be activated under commands of the AI agent to develop predictable actuations based on learned users behaviours and patterns which as example are repeated in the didactic week whilst are changed during the graduation days [56].

The main urban strategies developed are the following:

• Urban vs. Wilderness. Based on the existing formal system of the island there will be a strong contrast between urban condition and the wild part in the north and north-east. The existing nature is hereby preserved as authentic layer of the past. The campus is a densified evolution of old buildings, extensions as well as completely new constructions. The housing units will be scattered in nature and linked between each other by slightly elevated pathways. These are made with metal grids that do not seal the ground. Moreover, they give to the vegetation the possibility to merge with the new and keep walkability during different weather conditions;

• Generative Campo. The heart of the university will be a precisely circumscribed open space serving as a ‘trading zone’. A trading zone is a space for crossing, gathering and interaction. The reference for this spatial element is the Venetian ‘Campo’: the presence of wells is transformed into a landscape of water, stone and benches that provide the setting for intellectual exchange. The campo separates and connects the neighbouring building at the same time and refers to historical traces;

• Spatial Sequence. The perimeter of the urban form is reinforced by a spatial sequence. It accommodates different urban qualities that reach from ‘intimate retreat’ to ‘generous representation’. Above all, they connect different realms such as the outside world with the island, the wilderness with the urban and the northern with southern part. Different pavements distinguish the campo and the perimeter spaces: whereas the campo is paved with traditional stones, the others feature wood block surfaces that allow water to infiltrate into the ground.

The planning process is accompanied by an extensive Building Energy Model (BEM) study, based on dynamic simulation aimed at optimising buildings envelope and smart scheduling. The main challenge regarding an architectural intervention on Poveglia island is definitely its remoteness to the mainland. It requires additional efforts compared to conventional settings. Such efforts include first of all infrastructural measures to connect the island to water and electricity supply, sewage and IT systems besides the transport of construction materials by boat and the necessity for extra strong piled foundations.

It is of high importance to consider strategies that ensure a certain degree of self-sufficiency for the energy needed by the buildings. In this way, the initial high investment can be amortised by low running costs during the life-cycle of the project. The major concern is the energy supply and production which constitutes one of the most important factors to guarantee the operational life of the buildings in the remote island connected with immaterial resources to the nodes of the Lagoon. High standard for all buildings to attain excellent performances has been set.

Self-sufficiency does not imply, however, that the island should stand on its own. Quite the contrary, it should be connected as much as possible so that the island can provide benefits far beyond its own boundaries. To utilise the full potential of the island it is required to use the grid as a storage for solar electricity even though the load matching in the case of a University Campus is not a critical concern. In this way, Poveglia becomes a productive part of the lagoon and can be a role model for other islands that enter into the grid in the future development.

The decentralisation of the energy production is commonly referred to as ‘smart grid’ [65]. This term highlights the manifold positive implications of having variety of operational and energy measures including smart meters, smart appliances and renewable energy sources [66] integrated in a major system of smart management. The direct benefits are among others the quicker restoration of electricity after power disturbances [67], the reduced operations and management costs for utilities, the environmental impact reduction, and ultimately lower power costs for consumers [68].

The general approach adopted for the energy concept [69] can be divided in two main parts:

• The reduction of the demand side by high performance of components;

• The onsite generation of energy from renewable sources.

Considering the planning of an efficient settlement [70] the first measure to assume is to design the buildings to gain good volume-surface ratios and configure envelopes with a low thermal transmittance, to shrink the thermal transmission losses, secondly the implementation of efficient systems such as groundwater heat pumps that has been considered to provide energy to all the settlement with an electrical balance towards zero energy goal.

The electricity production is promoted through the integration of photovoltaic modules on the buildings to cover the energy demand during most of the year considering also the use of energy storage systems [71] with light green mobility [72] as transition to Zero Energy Emission Districts (ZEED) [73]. The roofing systems are conceived to install surfaces for renewable energy exploitation optimizing the slope and configuration and the settlement design.

Poveglia’s energy model provides an overall picture of results from different aspects: heating and cooling calculation of each building (both in real and fractional values), calculations of energy needed for electricity, equipment and Domestic Hot Water (DHW) and predictions of energy supply by photovoltaic systems [74] considering the technological solution as the preferred one when cost-optimal evaluation is concerned [75].

The underpinning idea of the research concerns the application of a 3-step grading system to both roof and facade. The three steps determine the current condition reaching from intact over damaged to destroyed state. By the combination of these two parameters, it can be stated that there are some buildings which cannot be restored without disproportional measures. The case of complete destruction applies, however, just to a small amount of buildings. The condition of the remaining ones will be the basis to articulate different strategies for their reuse.

The project in Poveglia aims at introducing the idea of the shelter as leitmotif relating back to the 3 categories which have been identified for the current state of the existing buildings. In this way each category ‒ desolate, damaged, intact ‒ corresponds to one approach, i.e., one type of shelter. The architectural articulation of the three types has been developed considering that different spaces with varying atmospheres should be able to provide different uses. Moreover, the existing buildings have been treated with care, yet through a contemporary approach [76]. Three approaches and corresponding types have been developed and conceptualized to propose new interventions in Poveglia, considering the natural and the built environment characteristics. The three approaches range from the preservation (1) to new construction (3) adopting suitable strategies to integrate existing buildings into new built solutions, to the development of new environments for students’ learning activities.

The first approach deals with the buildings which have preserved both facade and roof. Making full use of their potential main appearance and most of its physical fabric is preserved. The intervention consists of an insertion of a new nucleus inside the shell of the existing. The interference of the house-in-house principle creates a layering of spaces which is enhanced by the mediating function of the generated thresholds. Decisive openings allow more light to enter and mark the renewal of the building also on the exterior.

The second approach remedies the situation for the buildings which suffered the most: a second skin will create a covering layer all around the old parts and encase them completely with a transparent closure. The formerly collapsed roofs will be substituted with intermediate ceilings which can be easily regulated according to visual and acoustic comfort. The extension by the second skin increases the amount of usable space for academic activities.

The third approach provides further type of shelter which applies for all new constructions made on the island. It is mainly built in wood offering a warm and welcoming atmosphere. It can easily adapt to a wide range of spatial configurations reaching from housing units up to big gathering spaces for lectures, assemblies and large-scale events such as conferences, graduation days, PhD defence days, proclamation days.

In the following Table 1 the concept for refurbishment and new construction are summarized for each approach.

Finding the right balance can be complicated. In fact, the aim to keep the existing buildings is by nature diametrically opposed to pure contemporary requirements. Values are not universal and depend on the point of view: preservation is a matter of appreciation for historical entities [77], an attitude and by no means absolute necessity [78]. Differentiating between value and valorisation can be hereby a first step to get the situation under control [79]: whereas the term ‘to value’ implies the appreciation of existing, ‘valorising’ is intended as ‘giving added value’. That is to say that the specific values of the project are supplemented by ‘added values’ that should enhance and boost the first ones instead of diminish them [80].

Phenomena of innocuous colour and material alterations will be preserved since they are part of the material authenticity and can trigger age value. Internal partitions will be considered for the new layout, existing flooring and roofs kept were possible. These measures are indispensable to guarantee the aspired historical continuity not only as idea of the old but as tangible physical fabric. The crucial point is to make Poveglia’s architecture readable to the users which will enable the buildings to acquire and then to maintain sufficient appreciation for continuous care and future preservation.

The interior of the canteen recalls the spatial experience of being in a naturally formed cave. It surrounds the user entirely with a solid shell which gives you a unanimous tactile experience: rough, unpolished and primitive. The impression of an edgy space is obtained by triangle-shaped panels which unify ceiling and walls to a unique architectural language. Sun rays infiltrating a cave through narrow slots are simulated by stripes of light which are built in the joints of the panels to generate a diffuse illumination.

The planning of the new campus enhances the dialogue between old and new buildings in order to create a harmonious yet intriguing composition [81]. Traces of existing formal systems, such as the regular central square as well as remaining perimeter walls become the basis for new extensions [82]. Vice versa there are changes to the old buildings which originate in the adaption to the added buildings to keep a set of resilient proportions of volume and height. The open spaces that embrace the buildings follow the central issue of offering a stage to the public and facilitate heterogeneity and connectivity [83]. The social integration and cooperation are dominant issues [84] considering the campus as a user-centred learning environment [85].

There is something to the setting of the island: the abandoned ruins and the dominance of nature, they make one think about the essential things in life, the struggle for survival and the most basic needs for a primitive shelter. It is most probably the hostile exposure to rain, wind, fog and the isolation from the outside world. In this sense, Poveglia brings the visitor back to an old tale: the story of Laugier’s Adam as described in his Essay on Architecture published in 1755. The Abbé argued with his ‘Primitive Hut’ in favour of a man-made shelter that served as a meteorological defence in a solitary, individual experience. ‘Houses come before temples. (...) Pragmatism comes before ritual. Structure comes before space’ [86]. Compared to the proposed project, there are intriguing parallels to Laugier’s primordial scenario. Most notably there is the necessity of creating shelters for human activity in a difficult environment. The powerful imaginary of such a quest suggested the idea of shelter as guiding theme in the development of the architectural language [87] coupled with high performance standards [88]. Whereas in the tale everything is made ex-novo, Poveglia raises an additional question: what is the role of the existing, the ‘found-spaces’, as shelter?

Since its abandonment in 1968, buildings started to deteriorate progressively due to missing maintenance and the vandalism of occasional visitors. It was, however, a matter of time until the built fabric would give in to both alteration and serious decay.

The major factors for decay have been the exposure to weathering and the high level of humidity in the lagoon. Over the years many roofs have partly or completely collapsed. Finishing disintegrated and exposed brick or concrete surfaces directly to the rough conditions. Decomposing windows and doors enhanced the decay further on by allowing vegetation to enter. In addition, the soil has been chemically contaminated due to accumulation of waste and orphaned items. Signs of decay reach, moreover, from biological colonisation such as lichens, mosses and ferns, rust stains up to delamination and cracks in wood pieces, as well as spalling, efflorescence on both brick and concrete. Given this broad amount of decay and the restraint of evaluation sources the implementation of a simple but sound classification to assess the potential for reuse has been promoted [89].

Simulations have been performed in order to define the suitable building envelope to achieve good energy performance. Since the retrofit intervention includes three architectural typologies, it is necessary to have a precise definition on the exact material included in the project [64].

BEM allows to define the energy consumption of each building in the campus with the contribution of photovoltaic systems. The calculation engine used is Energy Plus by Lawrence Berkeley National Laboratory, USA and the solar electrical production is calculated by PVGIS portal by JRC – Joint Research Centre, Ispra (https://re.jrc.ec.europa.eu/pvg_tools/en/tools.html), the results are resumed in Figure 6 and Figure 7 where the positive energy balance of the buildings is shown.

It is possible to organize a new campus on an abandoned island applying a Net Zero Energy Building (NZEB) concept providing a new life to the buildings and changing the nature of the node which becomes attractive for people and active into producing energy.

Figure 7.

Energy consumption distribution of the University Campus in Poveglia

‘Maritime Oasis’ [36] creates a scenario in which the cognitive principle realized at eLUX lab is applied and extended to Poveglia Island university settlement [90]. The maritime environment suggests principles that cover a larger rehabilitation circle than on the mainland especially because of the heavily decayed buildings [91]. Figure 8 shows, for one sample building, the key data resulting from the simulation carried out: the percentage of energy for usage, the number of users and the monthly distribution of energy demand (kWh/month). Figure 9 shows for the topology of buildings “Mensa”, “Cafeteria”, “Faculty” and “Houses” the key data in terms of uses, occupancy, energy consumption distribution and configuration. Depending on the assumed occupancy profiles for the number of users considered for the different buildings the energy consumption distribution varies consistently depending on the use and the refurbished or new construction buildings.

Figure 8.

Monthly energy consumption (grey) and production (yellow) over one year

Figure 9.

Buildings in the University Campus: uses, occupancy, energy consumption distribution and configuration

The sensors will translate environmental conditions into data and deliver to Watson. After analysing the data, Watson will give commands to trigger direct actions from the actuators. As soon as sensors installed in classrooms detect a poor air quality, Watson will trigger a higher ventilation rate in order to improve the air quality in short response time. In another scenario, where too much people are waiting in an underground station, the access systems and signals could be reconfigured to manage the temporary peak of affluence maintaining a suitable level of service.

Users can exploit a dedicated mobile application to interact in real-time with both the information from Watson (translated into a user interface that has been designed according to rules for a better UX) and each other (an integrated inter-com service and social networking).

They can see the energy performance, the room comfort level or the occupancy rate of the buildings they are interested in, or even they can benefit from shared services provided by different university structures (e.g. canteen, library or even the equivalent services from other universities in the lagoon area). The users’ involvement could be beneficial to reduce the rebound effect and performance gap detected in NZEB buildings [92], [93] and achieve an actual result in reducing the energy consumption and the environmental impacts as well as to enhance and regenerate the place.

The sensors applied in the project are monitoring all parameters concerning the room comfort conditions. Additionally, sensors connected to weather forecast will allow Watson to monitor severe weather changes ahead. Internet traffic will be also monitored as part of the sensors applied in the project. As corresponding actions commanded by Watson, the actuators will regulate heating and cooling, activate humidifier or dehumidifier, open or close the shading devices, increase or decrease ventilation rate and also give alerts to users that their focused rooms are heavily occupied.

The role of the sensors and actuators on Poveglia Island is to empower the vision of a greater network of ‘Smart city and Smart campus’. Implementing these technologies in the design phase it is possible to simulate the response system in the use phase of the buildings. The connectivity and networking of both the facilities and the academic services will be shared within the greater network. It is somehow helping rejuvenating Venice and breaks the stereotype of being a ‘Senior city’. A vivid and vibrant public institution is definitely a good example for reutilisation project of abandoned islands in the lagoon area. Poveglia is the perfect place for testing a cognitive system that connects various spots in the Venetian Lagoon and reinforces the historical bond between the islands.

Installed actuators will respond in real time with incoming commands, which have been deduced, from sensors, user preferences and external data [94]. Virtual reality devices will help to simulate architectural interventions and help to facilitate maintenance based on Building Information Modelling (BIM) model for facility management. The settlement will be described by a Geographic Information System (GIS) model in which the university buildings and residential units are included and data managed at island level and building level.

As long as the buildings are operating, a smartphone application will be designed according the UX principles to facilitate the communication between users and the AI agent. The cognitive system needs to communicate to the users, as in general, over 90% of the data generated by IoT network are unstructured. Since the buildings are designed with high energy efficiency standard, one of the interface’s aims is to translate by AI the unstructured data and withdraw meanings from the data, in order to provide the users with comprehensive infographics, useful for understanding the functioning of the built environment.

Various academic institutions have been involved in the ‘Smart campus’ network. The University Campus imagined for Poveglia is encompassed in the scenario of an extension of Ca’ Foscari University, which could access the resources present on Poveglia Island. For the pan-lagoon area, an interface to visualise the application for different universities (e.g., VIU-Venice International University, Accademia and other Ca’ Foscari campuses) (Figure 10) has been designed on the basis of the eLUX bi-directional app [95].

Figure 10.

Mockup of the bi-directional App for the Cognitive Campus in Poveglia to collect and analyse the users’ feedback and provide information about building energy management