Taxonomy of Integrated Operation Centers

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This entry is adapted from the peer-reviewed paper 10.3390/su151411101

An Integrated Operation Center (IOC) is essential for efficient Smart Governance. An IOC is a centralized platform that integrates data from various sources and uses advanced analytics to provide real-time insights to help users make informed decisions. It acts as the central nervous system by integrating information and processes from various departments/sources to help officials manage and optimize city operations and infrastructure.

Smart City Integrated Operation Centers Humanitarian Computing Internet of Things

1. Introduction

Figure 1 shows a taxonomy of Integrated Operation Centers (IOCs) in SCs. The root is the IOC itself. The first-level branch shows the different methods of categorizing an IOC. They can be classified based on the number of functions or the type of functions they offer, the scope or areas covered by the IOC, the size of the IOC in terms of hardware and software, and the orientation of the IOC—how the IOC is configured to manage the incoming information.

Figure 1. Taxonomy for IOCs in SCs.

2. Function

Organizations and the government develop IOCs to serve specific functions. Some functions of IOCs are collecting and unifying data from various sources, automation, facilitating decision making, managing city services, enabling CCTV surveillance, crime prediction, and disaster preparation. Researchers' research shows that IOCs can further be classified by function based on the number or the type of function they offer.

2.1. Classification by Number of Functions

Based on the number of functions IOCs offer, they can be either single-function or multi-function IOCs. A single-function IOC (SFIOC) is an IOC designed to offer only one service. Bouleft et al. ^[1] proposed a cost-effective technique for waste collection that sends smart bins’ status to an IOC. The IOC then uses a hybridized genetic algorithm (GA) to plan a cost-effective schedule containing the route for waste collection. An SFIOC does not mean the IOC strictly carries out one function. Instead, it means that, although the IOC has one role in mind, it performs other low-priority functions. For example, Beg et al. ^[2] proposed a traffic system for Smart Cities, where UAVs, traffic lights, traffic police, and crowdsensing via Google Maps server help to manage the traffic system and expedite emergency responses. Thus, the primary function of the SFIOC is traffic system management, while emergency response is a secondary feature; if the primary function fails, the whole system fails.

Multi-function IOCs (MFIOCs), as the name implies, are IOCs that perform more than one function. They are more common than SFIOCs because of the multi-faceted requirements of cities. In ^[3], the authors report the success of the Tumakuru Command and Control Center. It is an example of a multi-function IOC that carries out environmental monitoring, solid waste management, emergency response system, and traffic management system. Governments prefer MFIOCs because they allow officials to integrate all departments and agencies into one entity, which enables collaboration and efficiency. A few companies, like Cisco Systems ^[4], Honeywell ^[5], and IBM ^[6], build IOCs that gather information from IoT devices, process it, and use it for several functions. However, other companies only focus on IOCs related to their product line. For instance, Hitachi’s IOC processes mainly video data ^[7]. It allows the company to incorporate its existing solutions into the IOC, thus reducing its production cost.

Both MFIOCs and SFIOCs have several benefits. On the one hand, MFIOCs are larger. Thus, they can integrate several departments and agencies into one virtual body, by which top officials have more control over government workings. It also increases the government’s agility since all government agencies (including citizens) are within reach. MFIOCs’ large size and complexity mean that more human resources are needed, which means more job opportunities for citizens.

On the other hand, SFIOCs are cheaper to develop. They can be the first step of a phased implementation of an MFIOC, which allows the public to observe its benefits and gain more supporters to move to the next phase. They are also easier to convert from one function to another because they are smaller than MFIOCs, have a less complex structure, and have fewer employees to train than MFIOCs. Furthermore, MFIOCs often have more layers of bureaucracy and a more rigid organizational structure, making it harder to implement changes. A case study ^[8] shows how the Indian government successfully converted the well-equipped Bhopal Integrated Command and Control Center from environmental monitoring IOC to a COVID-19 emergency response IOC.

2.2. Classification by Mode

Figure 1 shows that IOCs can also be classified according to the mode of interaction between the IOC and the Region of Interest (ROI). IOCs can have a passive or active mode of operation. Passive IOCs (PIOCs) do not directly alter their ROI. They do not dispatch professionals or control actuators. They only monitor, archive, and process data. Thus, they mainly function as decision support systems. In ^[9], the authors proposed a PIOC that uses virtual reality and blockchain technology to improve IOC performance. The system uses Hyperledger fabric blockchain technology ^[10] to record data from the environment. Then, a virtual reality system is used to visualize the data and help the government make informed decisions in real time. PIOCs are easy and cheap to develop and deploy. They also help in decision support and policy development. However, they are limited in their application since they can only gather data and process them.

Active IOCs (AIOCs) are a superset of PIOCs; all AIOCs have some passive components, but all PIOCs do not have any active ones. Thus, AIOCs conduct data acquisition and processing for decision support, and they also help officials actuate their decisions. Researchers did not include decision automation as a criterion because some decisions are legally required to be carried out by city officials. Moreover, the system’s maintenance is not a criterion because it is not part of its goals. There is more demand for AIOCs because they allow the coordination of activities on the ground. Figure 1 shows that there are three types AIOCs:

UnconnectedAIOCs: These are IOCs that monitor the environment but cannot directly control it. They are the earliest form of AIOCs. They aim to monitor the ROI and send instructions from a centralized area called a “War Room” ^[3]. Sometimes, they use Participatory Sensing or Mobile Crowd Sensing to cut costs. Participatory Sensing involves collecting data of interest with the help of willing individuals carrying mobile phones, while Mobile Crowd Sensing employs both explicit and implicit user participation and social media data ^[11]^[12]. In ^[13], the authors proposed an SIOC that uses Participatory Sensing, where citizens tag their valuables with Bluetooth beacons. When one of the items is stolen, the SIOC notifies the volunteering participants, who enable their phone’s Bluetooth device. The volunteers’ phones send sighting information of the item to the SIOC. Then, the SIOC dispatches police to investigate the case further. Unconnected AIOC also finds application in solid waste management: In ^[1], the authors proposed an AIOC for waste collection in SC. The system consists of smart bins that send their status to an IOC. The IOC uses a hybridized genetic algorithm (GA) to plan a cost-effective schedule containing the route to the full bins for a waste truck. This system is an Unconnected AIOC because it has no actuators that the IOC directly controls; the IOC cannot control either the trucks’ or the bins’ actions, like moving, locking, or emptying them. Unconnected AIOCs are easiest to maintain because of their low complexity. However, they have the slowest response time because they rely on boots on the ground, which makes it the least accurate system due to human errors.
Semi-ConnectedAIOCs: These AIOCs partly control the ROI directly and are partly controlled manually by boots on the ground. SCs resort to developing semi-connected AIOCs because connecting or automating some controls could be expensive, impossible, or illegal. Some researchers use a Human-in-the-Loop emergency response AIOC ^[14]^[15]. The authors used the CitySCAPE framework to develop an agent-based system consisting of sensor agents for monitoring the environment, inference agents that use algorithms to make decisions, and action agents that are a combination of actuators (e.g., alarms, valves, air conditioning, electric gates) and emergency responders. In this system, the IOC monitors the system and controls some parts of the ROI. Traffic management IOCs are also semi-connected AIOCs because the system can control traffic lights, dynamic management signs, and smart gates, but it cannot directly operate the drivers, passengers, and traffic police ^[16]. Semi-Connected AIOCs integrate existing systems (both connected and unconnected) into a unified system managed by the IOC. The authors in ^[16] proposed the use of the Integrated Centre of Urban Mobility (CIMU) in São Paulo to optimize the transport system of the city. The authors demonstrate how the CIMU will combine all the existing systems and departments through an IOC. They recommended open protocols to ensure openness and encourage creative solutions from the public. Although the semi-connected AIOC offers some control to the IOC officials, it cannot control the manual part of the system; it can only dispatch the police and advise the drivers and passengers. Thus, for the system’s proper functioning, the automated subsystem must account for the errors from the manual part.
FullyConnectedAIOCs: These AIOCs are connected and can remotely control all parts of the ROI. Some Fully Connected AIOCs find applications in cybersecurity IOCs, where they manage the ROI by determining who receives access to what resources. Xu et al. ^[17] proposed an example of a cybersecurity Fully Connected AIOC. They used an IOC to develop a Certificateless Designated Verifier Proxy Signature (CLDVPS) scheme, where the IOC has supreme command over the UAV and acts as the original signer; the Ground Control Station (GCS) is entrusted by the IOC to securely send missions to the UAV with the help of a Key Generator Center (KGC). Fully Connected AIOCs also find applications in intrusion detection and prevention systems. In ^[18], the authors developed a Security Information and Event Management (SIEM) to protect all IoT devices within an SC. The system gathers data from the IoT devices, indexes them, and stores them in an AIOC using Splunk Enterprise ^[19]. The system analyzes the data using rule-based and machine learning techniques for intrusion detection and prevention. However, privacy is an issue with this technique. They are widely used in Smart Buildings for access controls where all actuators (such as doors, lighting, and ventilation) are remotely accessible. There are some examples of fully connected AIOCs in energy management. Al Kindhi et al. ^[20] show that an IOC is necessary for the efficient maintenance and monitoring of public lighting. They developed a centralized web-based system for monitoring and controlling solar-powered and IoT-enabled garden streetlights, thus reducing emergency calls and manual patrol. Several papers show that a fully connected Energy Operation Center (EOC) can help public and private buildings save energy by up to 17%. Fully connected AIOCs achieved more efficient service provision since they control the whole system. However, they are expensive to build, especially in large cities.

PIOCs could be the initial development phase of AIOCs. They could also be research facilities for data acquisition. Research shows that PIOC can be converted to AIOC: the Bhopal Integrated Command and Control Center ^[8], which functions as an environmental monitoring system, was then converted to a COVID-19 emergency response AIOC. Moreover, an AIOC can be an MFIOC; the Tumakuru Command and Control Center consists of an environment-monitoring, solid waste management, emergency response, and traffic management system ^[3]. AIOCs are more complex than PIOCs. They require more staff to operate.

2.3. Classification by Number of Domains

In the context of SCs, a domain refers to a specific area or sector of urban life improvable through technology and data. Neirotti et al. ^[21] categorized SC domains into hard and soft. The earlier domains include energy, lighting, environment, transportation, buildings, healthcare, and safety, while the latter include education, society, government, and the economy. They propose six application domains for SCs, including natural resources and energy, transport and mobility, buildings, living, government, and economy and people, which address corresponding challenges. Later papers narrow the list to eight domains, as discussed in Section 1 and shown in Figure 2. They are Smart Economy, Smart Environment, Smart Governance, Smart Mobility, Smart Human/Smart People, Smart Living, Smart Healthcare, and Smart Industry and Production ^[22]^[23].

Figure 2. Hard Smart Cities’ domains.

An IOC can be domain-specific (DIOC) and cross-domain (CIOC). A DIOC is an IOC that focuses on one domain only. The Smart Environment domain consists of anything within the citizens’ surroundings: environment monitoring, surveillance, disaster and emergency response, security, and sanitation. A DIOC for environment monitoring is where sensors in the ROI send measurements like wind, temperature, atmospheric pressure, and humidity to the center where the data are cleaned and stored. The data are also processed to provide government officials the necessary information for decision making. In some countries, the law demands that public data be available to citizens, which encourages disruption in data analytics and the economy of the SC ^[24]. DIOCs for Smart Buildings also belong to the environment domain. Several companies now have off-the-shelf Smart Building IOC suites (see Table 1) ^[25]^[26]. A DIOC can perform a single function in the case of Bophal IOC ^[8] or be an MFIOC, like in the case of Tumakuru ^[3].

Table 1. High market capitalization companies with IOC solutions.

Ref.	Company	IOC Solution	Year	Area
^[4]	Cisco Systems	Cisco Kinetic for Cities ¹	2015	SC, SIP
^[5]	Honeywell	Honeywell City Suite Software	2020	SC
^[25]	Siemens	Building X, Xcelerator	2022	SB, SIP
^[6]	IBM	Intelligent Operations Center 5.2.3	2012	SC
^[27]	General Electric	Remote Operations Command Center	2021	SIP
^[28]	Schneider Electric	AVEVA Unified Operations Center	2019	SIP
^[7]	Hitachi	Hitachi Smart Spaces	2018	SC
^[29]	Motorola Solutions	Network and Security Operations Center	2021	SC
^[30]	Emerson Electric	iOps Workspace Solution	2014	SIP
^[26]	Johnson Controls	OpenBlue	2020	SB

SC = Smart City, SIP = Smart Industry and Production, and SB = Smart Building. ¹ Discontinued.

CIOCs are those IOCs that combine two or more domains. IBM’s InOC is an example of a CIOC, albeit it can serve as a DIOC ^[6]^[31]. The system has connection points where new applications can connect to the IOC, providing users the flexibility to expand the IOC’s functions. It can manage water management, public safety, transportation, social programs, entertainment venues, buildings, energy, healthcare, and more ^[31]. A CIOC brings together diverse staff from multiple domains. However, managing such a center can be challenging due to the many employees with different backgrounds. Therefore, the center cannot operate optimally without proper work protocols and staff training on collaboration across the domains. This inter-domain collaboration is crucial for the success of the CIOC. Although DIOCs are cheaper and easier to implement, they leave a communication gap for the decision makers. However, a CIOC can bridge this gap. It also shows the officials new dimensions and challenges that would be invisible otherwise.

3. Size

One can measure the size of an IOC by the number of citizens it services, the size of the area it covers, the complexity of operations it can perform, and its computing power (i.e., size, number, and complexity of hardware and software in the system). However, all four criteria are correlated; as the number of citizens or Regions of Interest (ROI) increase, the amount of hardware and software necessary to process the information timely and accurately increases.

Scientists have discussed the layers of IOCs. Prakash and Dattasmita ^[3] presented street IT infrastructure, Network, Data center, Application, and Integration layers, while India’s Ministry of Housing and Urban Affairs (MoHUA) combined the first two layers into one, as shown in Figure 3 ^[32]. This model considers the network layer as part of the street IT infrastructure. However, Fadli and Sumitra listed only three of the layers (i.e., sensor, network operation center/data center, and COC layer). Researchers adopt the MoHUA because their model has listed all the necessary components in a successful IOC.

Figure 3. IOC platform architecture.

Figure 3 shows the layers in the architecture of an IOC according to ^[32]. There are four layers: the data acquisition and collection layer (DACL), the data aggregation and analytics layer (DAAL), the business logic and application layer (BLAL), and the command and control layer (CCL). The DACL is in the ROI. It contains the sensors and actuators that improve citizens’ QoL. The DAAL collects, processes, and analyzes the data coming from the DACL. It uses advanced analytics tools and algorithms to identify patterns, trends, and anomalies, which enables informed decision making processes. The authors in ^[32] combined the Business Logic Layer and an Application Layer to form the BLAL. The Business Logic Layer is a component of software that contains the business logic or rules for how data are processed and managed within an application; the Application Layer is responsible for implementing specific business use cases, such as user authentication or data processing ^[33]. Both the DAAL and the BLAL are in the data center. The CCL is more like a presentation layer, where users access and visualize the data processed by the immediate BLAL and DAAL.

Moreover, the figure shows that the DACL is in the SC, the DAAL and BLAL are in the data center, and the CCL is in the command center, but this configuration may change. The data center is the heart of the IOC. It ties the DACL and the CCL together by collecting data from DACL, processing them, and sending the information to the CCL. Any change in the DACL’s or CCL’s size affects the data center’s size. When the area or service demand increases, more sensors are necessary for adequate sensing. This sensors increase causes an increase in the data generated, and the additional data require a higher data center. Likewise, an increase in the CCL’s functions increases the number of requests to the data center, which necessitates a data center upgrade to maintain the IOC’s performance. Hence, researchers classify the sizes of the IOCs according to the size of their data center.

Table 2 shows the four types of data centers. Each type corresponds to a specific size and level of redundancy. Tier 1 has the lowest configuration without redundancy, while Tier 4 has the highest with a fully fault-tolerant redundancy. Therefore, there are four types of IOCs based on their data center. These are micro, small, medium, or large. The Micro-IOC contains a Tier 1 data center or a single workstation. Typically, they manage Smart Buildings, as in ^[34], where the authors proposed an EOC that consists of a Building Information Modeling (BIM) and a Building Automation System (BAS). It achieved a 17% reduction in energy consumption. A Small IOC requires a Tier 2 data center. It can monitor and control larger environments, like hotels, stadiums, or public buildings. In ^[35], a small IOC (an EOC) uses Genetic Algorithm to save 9.44–15% of energy consumption of a South Korean City’s four public buildings: the office of the community center, the postal office, the police station, and the fire station. A Medium IOC uses a Tier 3 data center. Examples of their application are COC and MOC for small cities or IOC in the early phase of development. The large IOCs are for large cities that use a Tier 4 data center.

Table 2. Classification of data centers by tiers.

Parameters	Tier 1	Tier 2	Tier 3	Tier 4
Uptime guarantee	99.67%	99.74%	99.98%	100.00%
Downtime per year	<28.8 h	<22 h	<1.6 h	<26.3 min
Component redundancy	None	Partial	Full	Fault-tolerant
Concurrently maintainable	No	No	Partially	Yes
Price	Very Low	Low	High	Very High
Compartmentalization	No	No	No	Yes
Typical customer	Small businesses	Medium businesses	Large businesses	Large enterprises
Build Time	<3 Months	3–6 Months	15–20 Months	16–20 Months
Year first deployed	1965	1970	1985	1995

Large IOCs store and process more data. Thus, they improve the services of the SC. They also require more staff than their smaller counterparts. However, they are expensive to build and operate. They also have large data centers, typically Tier 3 or 4, consuming enormous amounts of energy, contributing to carbon emissions and climate change ^[36]. Although smaller IOCs have Tier 1 or 2 data centers or no data centers, their processing power limits their capabilities. Hence, they are only suitable for small areas.

4. Scope

Another way of classifying IOCs is by their scope. In this category, they can be classified into Private and Public IOCs. This classification also indicates the ownership of the center. The proprietary rights of an IOC affect its operations, privacy policy, and how the cities’ laws treat them and their data.

4.1. Private Integrated Operation Centers

As the name implies, companies or individuals own Private IOCs for their private applications. They monitor and control jurisdictions that are illegal for Public IOCs due to privacy. They find applications in privately owned buildings and industries. Several companies offer IOC suites for Smart Industry and Production applications ^[4]^[5]^[27]^[28]^[30]. They typically present a broad view of manufacturing, business processes, and infrastructure operations by combining information from different sources, which helps officials’ decision making.

In ^[35], the authors investigate the performance of EOC in a commercial building. In this case, the IOC and the data belong to the business owner. Shopping malls use IOCs to gain insight into customers’ preferences, control crowd distribution, improve customer experience, and increase sales ^[37]. IBM proposed an Entertainment Venue Operations Center (EVOC) that targets the entertainment industries, like a sports complex or stadium, cruise ship, theater, or concert hall ^[31]. An EVOC aims to improve the quality of entertainment and enhance the customer experience by improving crowd control, parking, and waiting time.

Private IOCs complement Public IOCs by improving the QoL of workers and customers that constitute the SC. They also improve the SC by collaborating with the government through information sharing or leasing part of their IoT network to the government. Researchers in ^[38] have demonstrated how smartphones can share livestream data with Public IOCs to improve the community’s security. Other benefits of Private IOCs are that they enable businesses to tailor services to customer needs. They also improve manufacturing performance and the coordination of daily activities by increasing collaboration between workers ^[39]. They also promote greater operational awareness, which in turn helps executives make informed decisions. Their improved crisis response ensures workers’ and citizens’ safety ^[39].

4.2. Public Integrated Operation Centers

Public IOCs belong to the community. In the case of South Sumatera, Indonesia ^[40], they are created by the laws or policies of the city’s legislature, which means that the city’s legislature decides to fund, regulate, or oversee the development and operation of Public IOCs in the SC. However, they are usually developed through special purpose vehicles (SPVs) in India ^[3]^[8]. Full-time CEOs head the SPVs, while the board contains nominees of the central government, government, and the Urban Local Bodies (ULBs). In this format, the government lends the SPV financial credibility, and it also helps in building infrastructure that benefits the public ^[3]. Other ways the government establishes Public IOCs are joint ventures, subsidiaries, public–private partnerships (PPP), or turnkey contracts.

Table 3 shows that COC and MOC are the same. The table shows that neither population nor area determines the center’s name. The difference in nomenclature depends on the country’s administrative terminology. Fadli and Sumitra ^[41] surveyed Bandung COC. Bandung is the capital of West Java Province, Indonesia. Bandung COC is for e-government applications. The DACL is a wireless network of audio and visual sensors, while the DAAL is hierarchical: the data center is at the top and the local government areas (SKPD) at the bottom. The SKPDs collect data from their subnet and send it to the data center for backup and processing. The CCL monitors the communities’ activities by monitoring the SKPDs’ performance reports. Another example of a COC is the Daejeon Smart City Operation Center in Daejeon City, South Korea. It is a security and emergency response IOC. It reduced the response time from 7.5 min to 6.0 min while decreasing the crime rate by 5.0% and increasing the arrest rate by 7.7%. However, COC projects have a history of delays. The Daejeon took 4 years to complete ^[42]. COC project delays are due to factors such as fundraising, budget constraints, and collaboration between various departments, which can lead to delays due to differences in priorities. Additionally, there are few Public IOC solutions in the market due to the market size and the large number of parameters to consider during development. Thus, tech companies often collaborate with the customer (i.e., the government) to design a system to accommodate their needs, which increases development price.

Table 3. List of COC and MOC in the literature.

Ref.	Country	City	Population	Area (km²)	Center
^[43]	Portugal	Porto	214,349	41.42	MOC
^[44]^[45]	Russia	Novgorod	218,717	229.28	MOC
^[3]	India	Tumakuru	302,143	44.47	MOC
^[46]	Indonesia	Jambi	702,209	205.38	MOC
^[42]	S. Korea	Daejeon	1,475,221	539.80	COC
^[47]	Brazil	Porto Alegre	1,483,771	496.00	MOC
^[24]	Spain	Barcelona	1,636,762	101.90	COC
^[8]	India	Bhopal	1,798,218	286.00	MOC
^[47]	Brazil	Belo Horizonte	2,501,576	331.00	MOC
^[48]	Indonesia	Bandung	2,575,478	167.70	COC
^[43]^[49]	Brazil	Rio de Janeiro	6,718,903	1221.00	MOC
^[24]	United Kingdom	London	9,126,366	1572.00	COC

4.3. Collaborations in Public Integrated Operation Centers

Meijer and Bolívar ^[50], define an SC as a city with smart collaboration, while Chun et al. define collaboration as “a process or set of activities in which two or more agents work together to achieve shared goals” ^[51]. Hence, although the primary goal of an IOC is to optimize services in an SC to improve QoL, they must also help improve collaboration between the government, citizens, and other stakeholders. Unlike the Private IOC, where the employees share a mission, vision, and culture and work towards the same goals, the Public IOC is more diverse, consisting of various government departments having different priorities, policies, and regulations, which can lead to conflicting interests and goals.

Figure 4 shows the types of collaboration a government can harness for a sustainable SC. The government can collaborate with citizens, organizations, and sectors to maximize the efficiency of the IOC.

Figure 4. Collaboration in Public IOCs.

Government–Citizen Collaboration (GCC) is when the government engages citizens in governance. This type of collaboration increases citizens’ trust and confidence in their government ^[47]. There are two types of GCCs: direct and indirect. A direct GCC is when citizens directly contribute to the IOC’s operations. Participatory sensing is an example of direct GCC, where the citizens use their smartphones to sense the environment and send the information to the IOCs. Papadakis et al. proposed a Bluetooth-based beacon attached to a stolen item that communicates with volunteering participants (i.e., citizens) ^[13]. The volunteers’ phones send sighting information of the item to the IOC, where police further investigate. Another form of direct GCC is Smart Governance: it is the engagement of various stakeholders in decision making and public services ^[47]. MOCs in Brazil use social media and the internet to communicate with citizens ^[52], while London uses open data to enable citizens to come up with solutions to the city’s pressing problems ^[24]. Indirect GCC is when citizens contribute to governance through their government representatives, who present those inputs at the IOC war room meetings ^[47]. Some of the concerns of GCC are ^[47]: (1) the digital divide excludes a large section of the citizens in the city’s development, (2) more demands by the citizens ^[47], and (3) difficulty in sensitizing the citizen on the role of the IOC, and the hows and why they should contribute.

Government–Organization Collaboration (GOC) is the relationship between the government and other government or non-government organizations to ensure the smooth working of the IOC. There are two main types of GOCs: internal and external collaborations. Internal GOC refers to the joint effort of government organizations to ensure an efficient IOC. It can be inter-agencies, inter-departmental, inter-organizational, or cross-collaboration within the government ^[47]. Interviews with IOC officials show that they emphasize collaboration in data sharing and decision making ^[47]^[52]^[53]. Internal collaboration can be at the data sharing level or the decision making level. At the data sharing level, the various departments access one another’s data. However, difficulty arises in this type of collaboration due to a lack of contextualization of the shared data ^[47]. Kushnareva et al. ^[44] cited an example of the lack of context awareness of meteorological (rainfall) data that failed to adjust water release plans, which caused a severe flood event in Brisbane, Australia. At the decision making level, IOCs have war rooms where government representatives deliberate on cases with significant political ramifications ^[47].

External collaboration refers to the cooperation of the Public IOC with non-governmental entities like civic groups, nonprofit organizations (NPOs), and for-profit organizations ^[52]. Researchers also refer to it as a cross-sectoral or inter-sectoral collaboration because it is a relationship between the public, private, and nonprofit sectors. Public–private partnership (PPP) allows the government to reach the vulnerable. An example is Daejeon IOC signing an agreement with private communications companies to provide emergency services to vulnerable groups, like children, patients with dementia, and senior citizens living alone ^[42]. Also, PPP helps the IOC reduce running costs. The authors in ^[54] cited how Rio de Janeiro IOC uses the Waze application to monitor the city’s traffic. However, due to the large number of cameras deployed in the city, the IOC collaborates with laboratories from the engineering school at the Federal University of Rio de Janeiro, which use AI algorithms to select the co-located cameras based on data from platforms like Waze ^[54]. This collaboration indicates the existence of a public–private-university relationship. Public–nonprofit partnership (PNP) is widely observed between EOCs and NPOs ^[55]^[56]. It allows them to contribute their quota to the city’s success by helping the IOC solve complex societal problems or overcoming socio-technical hurdles ^[57]. However, they have some challenges, such as privacy and other legal issues, lack of trust, conflicting interests, and coordination difficulties.

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